Patent Publication Number: US-2022214944-A1

Title: Optimized Selection of Participants in Distributed Data Rebuild/Verification

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     The present U.S. Utility Patent Application claims priority pursuant to 35 U. S.C. § 120, as a continuation-in-part of U.S. Utility patent application Ser. No. 17/066,873, entitled “OPTIMIZED SELECTION OF PARTICIPANTS IN DISTRIBUTED DATA REBUILD/VERIFICATION” filed Oct. 9, 2020, which claims priority pursuant to 35 U.S.C. § 120, as a continuation-in-part of U.S. Utility patent application Ser. No. 16/136,362, entitled “REMOTE STORAGE VERIFICATION,” filed Sep. 20, 2018, issued as U.S. Pat. No. 10,802,915 on Oct. 13, 2020, which is a continuation-in-part (CIP) of U.S. Utility patent application Ser. No. 15/285,582, entitled “SHARED OWNERSHIP OF NAMESPACE RANGES,” filed Oct. 5, 2016, issued as U.S. Pat. No. 10,372,350 on Aug. 6, 2019, which claims priority a continuation-in-part (CIP) of U.S. Utility patent application Ser. No. 13/291,030, entitled “PARTITIONING DATA FOR STORAGE IN A DISPERSED STORAGE NETWORK,” filed Nov. 7, 2011, issued as U.S. Pat. No. 9,483,398 on Nov. 1, 2016, which claims priority pursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No. 61/417,873, entitled “DATA REBUILDING IN A DISPERSED STORAGE NETWORK,” filed Nov. 29, 2010, all of which are hereby incorporated herein by reference in their entirety and made part of the present U.S. Utility Patent Application for all purposes. 
    
    
     STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
     Not Applicable. 
     INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC 
     Not Applicable. 
     BACKGROUND OF THE INVENTION 
     Technical Field of the Invention 
     This invention relates generally to computer networks and more particularly to dispersing error encoded data. 
     Description of Related Art 
     Computing devices are known to communicate data, process data, and/or store data. Such computing devices range from wireless smart phones, laptops, tablets, personal computers (PC), work stations, and video game devices, to data centers that support millions of web searches, stock trades, or on-line purchases every day. In general, a computing device includes a central processing unit (CPU), a memory system, user input/output interfaces, peripheral device interfaces, and an interconnecting bus structure. 
     As is further known, a computer may effectively extend its CPU by using “cloud computing” to perform one or more computing functions (e.g., a service, an application, an algorithm, an arithmetic logic function, etc.) on behalf of the computer. Further, for large services, applications, and/or functions, cloud computing may be performed by multiple cloud computing resources in a distributed manner to improve the response time for completion of the service, application, and/or function. For example, Hadoop is an open source software framework that supports distributed applications enabling application execution by thousands of computers. 
     In addition to cloud computing, a computer may use “cloud storage” as part of its memory system. As is known, cloud storage enables a user, via its computer, to store files, applications, etc. on an Internet storage system. The Internet storage system may include a RAID (redundant array of independent disks) system and/or a dispersed storage system that uses an error correction scheme to encode data for storage. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S) 
         FIG. 1  is a schematic block diagram of an embodiment of a computing system in accordance with the invention; 
         FIG. 2  is a schematic block diagram of an embodiment of a computing core in accordance with the invention; 
         FIG. 3  is a schematic block diagram of an embodiment of a distributed storage processing unit in accordance with the invention; 
         FIG. 4  is a schematic block diagram of an embodiment of a grid module in accordance with the invention; 
         FIG. 5  is a diagram of an example embodiment of error coded data slice creation in accordance with the invention; 
         FIG. 6  is a flowchart illustrating an example of verifying encoded data slices in accordance with the invention; 
         FIG. 7  is a flowchart illustrating another example of verifying encoded data slices in accordance with the invention; 
         FIG. 8  is a flowchart illustrating an example of selecting dispersed storage (DS) units in accordance with the invention; 
         FIG. 9A  is a flowchart illustrating an example of rebuilding an encoded data slice in accordance with the invention; 
         FIG. 9B  is a flowchart illustrating an example of generating an encrypted partial encoded data slice in accordance with the invention; 
         FIG. 9C  is a block diagram of a rebuilding module in accordance with the invention; 
         FIG. 9D  is a block diagram of another rebuilding module in accordance with the invention; 
         FIG. 10A  is a flowchart illustrating another example of rebuilding an encoded data slice in accordance with the invention; 
         FIG. 10B  is a flowchart illustrating an example of encrypting an encoded data slice partial in accordance with the invention; 
         FIG. 11A  is a flowchart illustrating another example of rebuilding an encoded data slice in accordance with the invention; 
         FIG. 11B  is another flowchart illustrating another example of encrypting an encoded data slice partial in accordance with the invention; 
         FIG. 12A  is a flowchart illustrating an example of assigning storage resources in accordance with the invention; 
         FIG. 12B  is a flowchart illustrating an example of selecting storage resources in accordance with the invention; 
         FIG. 13A  is a flowchart illustrating an example of storing an encoded data slice in accordance with the invention; 
         FIG. 13B  is a flowchart illustrating another example of storing an encoded data slice in accordance with the invention; 
         FIG. 14A  is a schematic block diagram of another embodiment of a computing system in accordance with the invention; 
         FIG. 14B  is a flowchart illustrating an example of storing data in accordance with the invention; 
         FIG. 14C  is a block diagram of a storing module in accordance with the invention; 
         FIG. 15A  is a schematic block diagram of another embodiment of a computing system in accordance with the invention; 
         FIG. 15B  is a flowchart illustrating another example of storing data in accordance with the invention; 
         FIG. 15C  is a flowchart illustrating another example of storing an encoded data slice in accordance with the invention; 
         FIG. 16A  is a schematic block diagram of another embodiment of a computing system in accordance with the invention; 
         FIG. 16B  is a flowchart illustrating another example of storing data in accordance with the invention; 
         FIG. 16C  is an algorithm illustrating an example of encoding data in accordance with the invention; 
         FIG. 16D  is a processing module task map illustrating an example of determining processing module assignments in accordance with the invention; 
         FIG. 16E  is a flowchart illustrating another example of storing an encoded data slice in accordance with the invention; 
         FIG. 17A  is a schematic block diagram of another embodiment of a computing system in accordance with the invention; 
         FIG. 17B  is a flowchart illustrating another example of storing data in accordance with the invention; 
         FIG. 17C  is an algorithm illustrating another example of encoding data in accordance with the invention; 
         FIG. 17D  is a dispersed storage (DS) unit task map illustrating another example of determining DS unit assignments in accordance with the invention; 
         FIG. 17E  is a flowchart illustrating another example of storing an encoded data slice in accordance with the invention; 
         FIG. 17F  is a flowchart illustrating another example of storing an encoded data slice in accordance with the invention; 
         FIG. 18A  is a schematic block diagram of an embodiment of a dispersed storage (DS) unit in accordance with the invention; 
         FIG. 18B  is a flowchart illustrating another example of storing an encoded data slice in accordance with the invention; 
         FIG. 18C  is a flowchart illustrating an example of retrieving an encoded data slice in accordance with the invention; 
         FIG. 19A  is a flowchart illustrating another example of storing an encoded data slice in accordance with the invention; 
         FIG. 19B  is a flowchart illustrating an example of transferring an encoded data slice in accordance with the invention; 
         FIG. 19C  is a block diagram of another storing module in accordance with the invention; and 
         FIG. 19D  is a block diagram of another storing module in accordance with the invention. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       FIG. 1  is a schematic block diagram of a computing system  10  that includes one or more of a first type of user devices  12 , one or more of a second type of user devices  14 , at least one distributed storage (DS) processing unit  16 , at least one DS managing unit  18 , at least one storage integrity processing unit  20 , and a distributed storage network (DSN) memory  22  coupled via a network  24 . The network  24  may include one or more wireless and/or wire lined communication systems; one or more private intranet systems and/or public internet systems; and/or one or more local area networks (LAN) and/or wide area networks (WAN). 
     The DSN memory  22  includes a plurality of distributed storage (DS) units  36  for storing data of the system. Each of the DS units  36  includes a processing module and memory and may be located at a geographically different site than the other DS units (e.g., one in Chicago, one in Milwaukee, etc.). 
     Each of the user devices  12 - 14 , the DS processing unit  16 , the DS managing unit  18 , and the storage integrity processing unit  20  may be a portable computing device (e.g., a social networking device, a gaming device, a cell phone, a smart phone, a personal digital assistant, a digital music player, a digital video player, a laptop computer, a handheld computer, a video game controller, and/or any other portable device that includes a computing core) and/or a fixed computing device (e.g., a personal computer, a computer server, a cable set-top box, a satellite receiver, a television set, a printer, a fax machine, home entertainment equipment, a video game console, and/or any type of home or office computing equipment). Such a portable or fixed computing device includes a computing core  26  and one or more interfaces  30 ,  32 , and/or  33 . An embodiment of the computing core  26  will be described with reference to  FIG. 2 . 
     With respect to the interfaces, each of the interfaces  30 ,  32 , and  33  includes software and/or hardware to support one or more communication links via the network  24  and/or directly. For example, interfaces  30  support a communication link (wired, wireless, direct, via a LAN, via the network  24 , etc.) between the first type of user device  14  and the DS processing unit  16 . As another example, DSN interface  32  supports a plurality of communication links via the network  24  between the DSN memory  22  and the DS processing unit  16 , the first type of user device  12 , and/or the storage integrity processing unit  20 . As yet another example, interface  33  supports a communication link between the DS managing unit  18  and any one of the other devices and/or units  12 ,  14 ,  16 ,  20 , and/or  22  via the network  24 . 
     In general and with respect to data storage, the system  10  supports three primary functions: distributed network data storage management, distributed data storage and retrieval, and data storage integrity verification. In accordance with these three primary functions, data can be distributedly stored in a plurality of physically different locations and subsequently retrieved in a reliable and secure manner regardless of failures of individual storage devices, failures of network equipment, the duration of storage, the amount of data being stored, attempts at hacking the data, etc. 
     The DS managing unit  18  performs distributed network data storage management functions, which include establishing distributed data storage parameters, performing network operations, performing network administration, and/or performing network maintenance. The DS managing unit  18  establishes the distributed data storage parameters (e.g., allocation of virtual DSN memory space, distributed storage parameters, security parameters, billing information, user profile information, etc.) for one or more of the user devices  12 - 14  (e.g., established for individual devices, established for a user group of devices, established for public access by the user devices, etc.). For example, the DS managing unit  18  coordinates the creation of a vault (e.g., a virtual memory block) within the DSN memory  22  for a user device (for a group of devices, or for public access). The DS managing unit  18  also determines the distributed data storage parameters for the vault. In particular, the DS managing unit  18  determines a number of slices (e.g., the number that a data segment of a data file and/or data block is partitioned into for distributed storage) and a read threshold value (e.g., the minimum number of slices required to reconstruct the data segment). 
     As another example, the DS managing module  18  creates and stores, locally or within the DSN memory  22 , user profile information. The user profile information includes one or more of authentication information, permissions, and/or the security parameters. The security parameters may include one or more of encryption/decryption scheme, one or more encryption keys, key generation scheme, and data encoding/decoding scheme. 
     As yet another example, the DS managing unit  18  creates billing information for a particular user, user group, vault access, public vault access, etc. For instance, the DS managing unit  18  tracks the number of times a user accesses a private vault and/or public vaults, which can be used to generate a per-access bill. In another instance, the DS managing unit  18  tracks the amount of data stored and/or retrieved by a user device and/or a user group, which can be used to generate a per-data-amount bill. 
     The DS managing unit  18  also performs network operations, network administration, and/or network maintenance. As at least part of performing the network operations and/or administration, the DS managing unit  18  monitors performance of the devices and/or units of the system  10  for potential failures, determines the devices and/or unit&#39;s activation status, determines the devices&#39; and/or units&#39; loading, and any other system level operation that affects the performance level of the system  10 . For example, the DS managing unit  18  receives and aggregates network management alarms, alerts, errors, status information, performance information, and messages from the devices  12 - 14  and/or the units  16 ,  20 ,  22 . For example, the DS managing unit  18  receives a simple network management protocol (SNMP) message regarding the status of the DS processing unit  16 . 
     The DS managing unit  18  performs the network maintenance by identifying equipment within the system  10  that needs replacing, upgrading, repairing, and/or expanding. For example, the DS managing unit  18  determines that the DSN memory  22  needs more DS units  36  or that one or more of the DS units  36  needs updating. 
     The second primary function (i.e., distributed data storage and retrieval) begins and ends with a user device  12 - 14 . For instance, if a second type of user device  14  has a data file  38  and/or data block  40  to store in the DSN memory  22 , it send the data file  38  and/or data block  40  to the DS processing unit  16  via its interface  30 . As will be described in greater detail with reference to  FIG. 2 , the interface  30  functions to mimic a conventional operating system (OS) file system interface (e.g., network file system (NFS), flash file system (FFS), disk file system (DFS), file transfer protocol (FTP), web-based distributed authoring and versioning (WebDAV), etc.) and/or a block memory interface (e.g., small computer system interface (SCSI), internet small computer system interface (iSCSI), etc.). In addition, the interface  30  may attach a user identification code (ID) to the data file  38  and/or data block  40 . 
     The DS processing unit  16  receives the data file  38  and/or data block  40  via its interface  30  and performs a distributed storage (DS) process  34  thereon (e.g., an error coding dispersal storage function). The DS processing  34  begins by partitioning the data file  38  and/or data block  40  into one or more data segments, which is represented as Y data segments. For example, the DS processing  34  may partition the data file  38  and/or data block  40  into a fixed byte size segment (e.g., 21 to 2n bytes, where n=&gt;2) or a variable byte size (e.g., change byte size from segment to segment, or from groups of segments to groups of segments, etc.). 
     For each of the Y data segments, the DS processing  34  error encodes (e.g., forward error correction (FEC), information dispersal algorithm, or error correction coding) and slices (or slices then error encodes) the data segment into a plurality of error coded (EC) data slices  42 - 48 , which is represented as X slices per data segment. The number of slices (X) per segment, which corresponds to a number of pillars n, is set in accordance with the distributed data storage parameters and the error coding scheme. For example, if a Reed-Solomon (or other FEC scheme) is used in an n/k system, then a data segment is divided into n slices, where k number of slices is needed to reconstruct the original data (i.e., k is the threshold). As a few specific examples, the n/k factor may be 5/3; 6/4; 8/6; 8/5; 16/10. 
     For each slice  42 - 48 , the DS processing unit  16  creates a unique slice name and appends it to the corresponding slice  42 - 48 . The slice name includes universal DSN memory addressing routing information (e.g., virtual memory addresses in the DSN memory  22 ) and user-specific information (e.g., user ID, file name, data block identifier, etc.). 
     The DS processing unit  16  transmits the plurality of EC slices  42 - 48  to a plurality of DS units  36  of the DSN memory  22  via the DSN interface  32  and the network  24 . The DSN interface  32  formats each of the slices for transmission via the network  24 . For example, the DSN interface  32  may utilize an internet protocol (e.g., TCP/IP, etc.) to packetize the slices  42 - 48  for transmission via the network  24 . 
     The number of DS units  36  receiving the slices  42 - 48  is dependent on the distributed data storage parameters established by the DS managing unit  18 . For example, the DS managing unit  18  may indicate that each slice is to be stored in a different DS unit  36 . As another example, the DS managing unit  18  may indicate that like slice numbers of different data segments are to be stored in the same DS unit  36 . For example, the first slice of each of the data segments is to be stored in a first DS unit  36 , the second slice of each of the data segments is to be stored in a second DS unit  36 , etc. In this manner, the data is encoded and distributedly stored at physically diverse locations to improved data storage integrity and security. Further examples of encoding the data segments will be provided with reference to one or more of  FIGS. 2-9 . 
     Each DS unit  36  that receives a slice  42 - 48  for storage translates the virtual DSN memory address of the slice into a local physical address for storage. Accordingly, each DS unit  36  maintains a virtual to physical memory mapping to assist in the storage and retrieval of data. 
     The first type of user device  12  performs a similar function to store data in the DSN memory  22  with the exception that it includes the DS processing. As such, the device  12  encodes and slices the data file and/or data block it has to store. The device then transmits the slices  11  to the DSN memory via its DSN interface  32  and the network  24 . 
     For a second type of user device  14  to retrieve a data file or data block from memory, it issues a read command via its interface  30  to the DS processing unit  16 . The DS processing unit  16  performs the DS processing  34  to identify the DS units  36  storing the slices of the data file and/or data block based on the read command. The DS processing unit  16  may also communicate with the DS managing unit  18  to verify that the user device  14  is authorized to access the requested data. 
     Assuming that the user device is authorized to access the requested data, the DS processing unit  16  issues slice read commands to at least a threshold number of the DS units  36  storing the requested data (e.g., to at least  10  DS units for a  16 / 10  error coding scheme). Each of the DS units  36  receiving the slice read command, verifies the command, accesses its virtual to physical memory mapping, retrieves the requested slice, or slices, and transmits it to the DS processing unit  16 . 
     Once the DS processing unit  16  has received a read threshold number of slices for a data segment, it performs an error decoding function and de-slicing to reconstruct the data segment. When Y number of data segments has been reconstructed, the DS processing unit  16  provides the data file  38  and/or data block  40  to the user device  14 . Note that the first type of user device  12  performs a similar process to retrieve a data file and/or data block. 
     The storage integrity processing unit  20  performs the third primary function of data storage integrity verification. In general, the storage integrity processing unit  20  periodically retrieves slices  45 , and/or slice names, of a data file or data block of a user device to verify that one or more slices have not been corrupted or lost (e.g., the DS unit failed). The retrieval process mimics the read process previously described. 
     If the storage integrity processing unit  20  determines that one or more slices is corrupted or lost, it rebuilds the corrupted or lost slice(s) in accordance with the error coding scheme. The storage integrity processing unit  20  stores the rebuilt slice, or slices, in the appropriate DS unit(s)  36  in a manner that mimics the write process previously described. 
       FIG. 2  is a schematic block diagram of an embodiment of a computing core  26  that includes a processing module  50 , a memory controller  52 , main memory  54 , a video graphics processing unit  55 , an input/output (IO) controller  56 , a peripheral component interconnect (PCI) interface  58 , at least one IO device interface module  62 , a read only memory (ROM) basic input output system (BIOS)  64 , and one or more memory interface modules. The memory interface module(s) includes one or more of a universal serial bus (USB) interface module  66 , a host bus adapter (HBA) interface module  68 , a network interface module  70 , a flash interface module  72 , a hard drive interface module  74 , and a DSN interface module  76 . Note the DSN interface module  76  and/or the network interface module  70  may function as the interface  30  of the user device  14  of  FIG. 1 . Further note that the  10  device interface module  62  and/or the memory interface modules may be collectively or individually referred to as 10 ports. 
       FIG. 3  is a schematic block diagram of an embodiment of a dispersed storage (DS) processing module  34  of user device  12  and/or of the DS processing unit  16 . The DS processing module  34  includes a gateway module  78 , an access module  80 , a grid module  82 , and a storage module  84 . The DS processing module  34  may also include an interface  30  and the DSnet interface  32  or the interfaces  68  and/or  70  may be part of user  12  or of the DS processing unit  14 . The DS processing module  34  may further include a bypass/feedback path between the storage module  84  to the gateway module  78 . Note that the modules  78 - 84  of the DS processing module  34  may be in a single unit or distributed across multiple units. 
     In an example of storing data, the gateway module  78  receives an incoming data object that includes a user ID field  86 , an object name field  88 , and the data field  40  and may also receive corresponding information that includes a process identifier (e.g., an internal process/application ID), metadata, a file system directory, a block number, a transaction message, a user device identity (ID), a data object identifier, a source name, and/or user information. The gateway module  78  authenticates the user associated with the data object by verifying the user ID  86  with the managing unit  18  and/or another authenticating unit. 
     When the user is authenticated, the gateway module  78  obtains user information from the management unit  18 , the user device, and/or the other authenticating unit. The user information includes a vault identifier, operational parameters, and user attributes (e.g., user data, billing information, etc.). A vault identifier identifies a vault, which is a virtual memory space that maps to a set of DS storage units  36 . For example, vault  1  (i.e., user  1 &#39;s DSN memory space) includes eight DS storage units (X=8 wide) and vault  2  (i.e., user  2 &#39;s DSN memory space) includes sixteen DS storage units (X=16 wide). The operational parameters may include an error coding algorithm, the width n (number of pillars X or slices per segment for this vault), a read threshold T, a write threshold, an encryption algorithm, a slicing parameter, a compression algorithm, an integrity check method, caching settings, parallelism settings, and/or other parameters that may be used to access the DSN memory layer. 
     The gateway module  78  uses the user information to assign a source name  35  to the data. For instance, the gateway module  60  determines the source name  35  of the data object  40  based on the vault identifier and the data object. For example, the source name may contain a file identifier (ID), a vault generation number, a reserved field, and a vault identifier (ID). As another example, the gateway module  78  may generate the file ID based on a hash function of the data object  40 . Note that the gateway module  78  may also perform a message conversion, protocol conversion, electrical conversion, optical conversion, access control, user identification, user information retrieval, traffic monitoring, statistics generation, configuration, management, and/or source name determination. 
     The access module  80  receives the data object  40  and creates a series of data segments  1  through Y  90 - 92  in accordance with a data storage protocol (e.g., file storage system, a block storage system, and/or an aggregated block storage system). The number of segments Y may be chosen or randomly assigned based on a selected segment size and the size of the data object. For example, if the number of segments is chosen to be a fixed number, then the size of the segments varies as a function of the size of the data object. For instance, if the data object is an image file of 4,194,304 eight bit bytes (e.g., 33,554,432 bits) and the number of segments Y=131,072, then each segment is 256 bits or 32 bytes. As another example, if segment sized is fixed, then the number of segments Y varies based on the size of data object. For instance, if the data object is an image file of 4,194,304 bytes and the fixed size of each segment is 4,096 bytes, the then number of segments Y=1,024. Note that each segment is associated with the same source name. 
     The grid module  82  receives the data segments and may manipulate (e.g., compression, encryption, cyclic redundancy check (CRC), etc.) each of the data segments before performing an error coding function of the error coding dispersal storage function to produce a pre-manipulated data segment. After manipulating a data segment, if applicable, the grid module  82  error encodes (e.g., Reed-Solomon, Convolution encoding, Trellis encoding, etc.) the data segment or manipulated data segment into X error coded data slices  42 - 44 . 
     The value X, or the number of pillars (e.g., X=16), is chosen as a parameter of the error coding dispersal storage function. Other parameters of the error coding dispersal function include a read threshold T, a write threshold W, etc. The read threshold (e.g., T=10, when X=16) corresponds to the minimum number of error-free error coded data slices required to reconstruct the data segment. In other words, the DS processing module  34  can compensate for X-T (e.g., 16−10=6) missing error coded data slices per data segment. The write threshold W corresponds to a minimum number of DS storage units that acknowledge proper storage of their respective data slices before the DS processing module indicates proper storage of the encoded data segment. Note that the write threshold is greater than or equal to the read threshold for a given number of pillars (X). 
     For each data slice of a data segment, the grid module  82  generates a unique slice name  37  and attaches it thereto. The slice name  37  includes a universal routing information field and a vault specific field and may be  48  bytes (e.g., 24 bytes for each of the universal routing information field and the vault specific field). As illustrated, the universal routing information field includes a slice index, a vault ID, a vault generation, and a reserved field. The slice index is based on the pillar number and the vault ID and, as such, is unique for each pillar (e.g., slices of the same pillar for the same vault for any segment will share the same slice index). The vault specific field includes a data name, which includes a file ID and a segment number (e.g., a sequential numbering of data segments  1 -Y of a simple data object or a data block number). 
     Prior to outputting the error coded data slices of a data segment, the grid module may perform post-slice manipulation on the slices. If enabled, the manipulation includes slice level compression, encryption, CRC, addressing, tagging, and/or other manipulation to improve the effectiveness of the computing system. 
     When the error coded data slices of a data segment are ready to be outputted, the grid module  82  determines which of the DS storage units  36  will store the EC data slices based on a dispersed storage memory mapping associated with the user&#39;s vault and/or DS storage unit attributes. The DS storage unit attributes may include availability, self-selection, performance history, link speed, link latency, ownership, available DSN memory, domain, cost, a prioritization scheme, a centralized selection message from another source, a lookup table, data ownership, and/or any other factor to optimize the operation of the computing system. Note that the number of DS storage units  36  is equal to or greater than the number of pillars (e.g., X) so that no more than one error coded data slice of the same data segment is stored on the same DS storage unit  36 . Further note that EC data slices of the same pillar number but of different segments (e.g., EC data slice  1  of data segment  1  and EC data slice  1  of data segment  2 ) may be stored on the same or different DS storage units  36 . 
     The storage module  84  performs an integrity check on the outbound encoded data slices and, when successful, identifies a plurality of DS storage units based on information provided by the grid module  82 . The storage module  84  then outputs the encoded data slices  1  through X of each segment  1  through Y to the DS storage units  36 . Each of the DS storage units  36  stores its EC data slice(s) and maintains a local virtual DSN address to physical location table to convert the virtual DSN address of the EC data slice(s) into physical storage addresses. 
     In an example of a read operation, the user device  12  and/or  14  sends a read request to the DS processing unit  14 , which authenticates the request. When the request is authentic, the DS processing unit  14  sends a read message to each of the DS storage units  36  storing slices of the data object being read. The slices are received via the DSnet interface  32  and processed by the storage module  84 , which performs a parity check and provides the slices to the grid module  82  when the parity check was successful. The grid module  82  decodes the slices in accordance with the error coding dispersal storage function to reconstruct the data segment. The access module  80  reconstructs the data object from the data segments and the gateway module  78  formats the data object for transmission to the user device. 
       FIG. 4  is a schematic block diagram of an embodiment of a grid module  82  that includes a control unit  73 , a pre-slice manipulator  75 , an encoder  77 , a slicer  79 , a post-slice manipulator  81 , a pre-slice de-manipulator  83 , a decoder  85 , a de-slicer  87 , and/or a post-slice de-manipulator  89 . Note that the control unit  73  may be partially or completely external to the grid module  82 . For example, the control unit  73  may be part of the computing core at a remote location, part of a user device, part of the DS managing unit  18 , or distributed amongst one or more DS storage units. 
     In an example of write operation, the pre-slice manipulator  75  receives a data segment  90 - 92  and a write instruction from an authorized user device. The pre-slice manipulator  75  determines if pre-manipulation of the data segment  90 - 92  is required and, if so, what type. The pre-slice manipulator  75  may make the determination independently or based on instructions from the control unit  73 , where the determination is based on a computing system-wide predetermination, a table lookup, vault parameters associated with the user identification, the type of data, security requirements, available DSN memory, performance requirements, and/or other metadata. 
     Once a positive determination is made, the pre-slice manipulator  75  manipulates the data segment  90 - 92  in accordance with the type of manipulation. For example, the type of manipulation may be compression (e.g., Lempel-Ziv-Welch, Huffman, Golomb, fractal, wavelet, etc.), signatures (e.g., Digital Signature Algorithm (DSA), Elliptic Curve DSA, Secure Hash Algorithm, etc.), watermarking, tagging, encryption (e.g., Data Encryption Standard, Advanced Encryption Standard, etc.), adding metadata (e.g., time/date stamping, user information, file type, etc.), cyclic redundancy check (e.g., CRC 32 ), and/or other data manipulations to produce the pre-manipulated data segment. 
     The encoder  77  encodes the pre-manipulated data segment  92  using a forward error correction (FEC) encoder (and/or other type of erasure coding and/or error coding) to produce an encoded data segment  94 . The encoder  77  determines which forward error correction algorithm to use based on a predetermination associated with the user&#39;s vault, a time based algorithm, user direction, DS managing unit direction, control unit direction, as a function of the data type, as a function of the data segment  92  metadata, and/or any other factor to determine algorithm type. The forward error correction algorithm may be Golay, Multidimensional parity, Reed-Solomon, Hamming, Bose Ray Chauduri Hocquenghem (BCH), Cauchy-Reed-Solomon, or any other FEC encoder. Note that the encoder  77  may use a different encoding algorithm for each data segment  92 , the same encoding algorithm for the data segments  92  of a data object, or a combination thereof. 
     The encoded data segment  94  is of greater size than the data segment  92  by the overhead rate of the encoding algorithm by a factor of X/T, where X is the width or number of slices, and T is the read threshold. In this regard, the corresponding decoding process can accommodate at most X-T missing EC data slices and still recreate the data segment  92 . For example, if X=16 and T=10, then the data segment  92  will be recoverable as long as 10 or more EC data slices per segment are not corrupted. 
     The slicer  79  transforms the encoded data segment  94  into EC data slices in accordance with the slicing parameter from the vault for this user and/or data segment  92 . For example, if the slicing parameter is X=16, then the slicer  79  slices each encoded data segment  94  into 16 encoded slices. 
     The post-slice manipulator  81  performs, if enabled, post-manipulation on the encoded slices to produce the EC data slices. If enabled, the post-slice manipulator  81  determines the type of post-manipulation, which may be based on a computing system-wide predetermination, parameters in the vault for this user, a table lookup, the user identification, the type of data, security requirements, available DSN memory, performance requirements, control unit directed, and/or other metadata. Note that the type of post-slice manipulation may include slice level compression, signatures, encryption, CRC, addressing, watermarking, tagging, adding metadata, and/or other manipulation to improve the effectiveness of the computing system. 
     In an example of a read operation, the post-slice de-manipulator  89  receives at least a read threshold number of EC data slices and performs the inverse function of the post-slice manipulator  81  to produce a plurality of encoded slices. The de-slicer  87  de-slices the encoded slices to produce an encoded data segment  94 . The decoder  85  performs the inverse function of the encoder  77  to recapture the data segment  90 - 92 . The pre-slice de-manipulator  83  performs the inverse function of the pre-slice manipulator  75  to recapture the data segment  90 - 92 . 
       FIG. 5  is a diagram of an example of slicing an encoded data segment  94  by the slicer  79 . In this example, the encoded data segment  94  includes thirty-two bits, but may include more or less bits. The slicer  79  disperses the bits of the encoded data segment  94  across the EC data slices in a pattern as shown. As such, each EC data slice does not include consecutive bits of the data segment  94  reducing the impact of consecutive bit failures on data recovery. For example, if EC data slice  2  (which includes bits 1, 5, 9, 13, 17, 25, and 29) is unavailable (e.g., lost, inaccessible, or corrupted), the data segment can be reconstructed from the other EC data slices (e.g., 1, 3 and 4 for a read threshold of 3 and a width of 4). 
       FIG. 6  is a flowchart illustrating an example of verifying encoded data slices. A method begins with step  102  where a processing module (e.g., of a dispersed storage (DS) unit) determines a slice name of an encoded data slice to verify. The determination may be based on one or more of an error message, a request, a next slice name in a test list, a random slice name, a slice name associated with a local DS unit, and a rebuild slice process conclusion indicator. For example, a processing module determines a slice name associated with an encoded data slice to verify when the encoded data slice has been rebuilt. 
     The method continues at step  104  where the processing module obtains the encoded data slice and compresses the encoded data slice to produce a compressed encoded data slice. The obtaining may be based on one or more of retrieving the encoded data slice from a local memory, receiving the encoded data slice in response to sending a read slice request to a DS unit, and receiving the encoded data slice from a DS processing unit. The compressing may include one or more of determining compression information and compressing the encoded data slice in accordance with the compression information. The compression information may include one or more of a compression algorithm identifier (ID), a portion indicator, and a number of bits indicator. The determining of the compression information may be based on one or more of a lookup, a request, a command, and a data type. The compressing may include selecting a portion of the encoded data slice that includes all the bits of the encoded data slice, less than all of the bits of the encoded data slice, a random portion of the bits of the encoded data slice, and a predetermined portion of the bits of the encoded data slice. 
     The method continues at step  106  where the processing module determines a storage set of DS units associated with the slice name. The determination may be based on one or more of generating all slice names of all pillars associated with the slice name, a virtual dispersed storage network (DSN) to physical location table lookup, a predetermination, a message, and a command. The method continues at step  108  where the processing module sends compressed encoded data slice partial request messages to the storage set of DS units. The processing module may not send a compressed encoded data slice partial request message to a DS unit affiliated with the slice name (e.g., a current DS unit). The request may include one or more of a slice name corresponding to an encoded data slice affiliated with a recipient DS unit of the stored set of DS units, the compression information, a recipient DS unit ID, an initiator DS unit ID, and the slice name. 
     The method continues at step  110  where the processing module receives at least a decode threshold number of compressed encoded data slice partial response messages to produce compressed encoded data slice partials. The response messages may include one or more of a slice name corresponding to the encoded data slice associated with a DS unit of the response, the compression information, and a compressed encoded data slice partial associated with a DS unit of the response. The compressed encoded data slice partial is with reference to the encoded data slice and the encoded data slice associated with the DS unit of the response. 
     The method continues at step  112  where the processing module determines whether a sum (e.g., finite field math utilizing an XOR logical function) of the compressed encoded data slice partials compares favorably to the compressed encoded data slice. The processing module determines that the comparison is favorable when the sum of the compressed encoded data slice partials is substantially the same as the compressed encoded data slice. The method branches to step  116  when the processing module determines that the comparison is favorable. The method continues to step  114  when the processing module determines that the comparison is not favorable. 
     The method continues at step  114  where the processing module indicates a failed test when the processing module determines that the sum of the compressed encoded data slice partials does not compare favorably to the compressed encoded data slice. The failed test indication may include one or more of sending a failed test message, marking a list, facilitating rebuilding of the encoded data slice, and initiating another verification process. In addition, the method may repeat back to step  102  to verify another encoded data slice. 
     The method continues at step  116  where the processing module indicates a passed test when the processing module determines that the sum of the compressed encoded data slice partials compares favorably to the compressed encoded data slice. The passed test indication may include one or more of sending a passed test message, marking a list, and initiating another verification process. In addition, the method may repeat back to step  102  to verify another encoded data slice. 
       FIG. 7  is a flowchart illustrating another example of verifying encoded data slices, which include similar steps to  FIG. 6 . The method begins with steps  102 - 112  of  FIG. 6  where a processing module (e.g., of a dispersed storage (DS) unit) determines a slice name of an encoded data slice to verify, obtains the encoded data slice and compresses the encoded data slice to produce a compressed encoded data slice, determines a storage set of DS units associated with the slice name, sends compressed encoded data slice partial request messages to the storage set of DS units, receives at least a decode threshold number of compressed encoded data slice partial response messages to produce compressed encoded data slice partials, and determines whether a sum (e.g., finite field math utilizing an XOR logical function) of the compressed encoded data slice partials compares favorably to the compressed encoded data slice. The method branches to step  118  when the processing module determines that the comparison is favorable. The method continues to step  114  of  FIG. 6  when the processing module determines that the comparison is not favorable. The method continues at step  114  of  FIG. 6  where the processing module indicates a failed test when the processing module determines that the comparison is not favorable. 
     The method continues at step  118  where the processing module determines a DS unit of the stored set of DS units to produce a selected DS unit when the processing module determines that the sum of the compressed encoded data slice partials compares favorably to the compressed encoded data slice. The determination may be based on one or more of a random pick, a DS unit with a favorable comparison to selection criteria (e.g., high trust, high reliability, highly available, low latency, etc.), next in a DS unit list, and a DS unit that is not storing the encoded data slice (e.g., rather stores another encoded data slice of a set of encoded data slices wherein the set includes the encoded data). The method continues at step  120  where processing module sends a compressed encoded data slice request message to the selected DS unit. The method continues at step  122  where the processing module receives a compressed encoded data slice response message to produce a selected compressed encoded data slice. 
     The method continues at step  124  where the processing module generates a compressed encoded data slice partial of the encoded data slice. The generation includes partial decoding the encoded data slice to produce a vector utilizing an inverted square encoding matrix (e.g., dimensionally a decode threshold by the decode threshold) multiplied by the encoded data slice, partial encoding the vector to produce an encoded data slice partial utilizing an encoding matrix (e.g., only utilizing a row affiliated with an encoded data slice associated with the selected DS unit) multiplied by the vector, and compressing the encoded data slice partial to produce the compressed encoded data slice partial in accordance with compression information. 
     The method continues at step  126  where the processing module determines whether a sum (e.g., finite field math utilizing an XOR logical function) of compressed encoded data slice partials compares favorably to the selected compressed encoded data slice wherein compressed encoded data slice partials of the sum of the compressed encoded data slice partials includes the compressed encoded data slice partial of the encoded data slice and excludes a compressed encoded data slice partial associated with the selected DS unit. The processing module determines that the comparison is favorable when the sum of the compressed encoded data slice partials is substantially the same as the selected compressed encoded data slice. The method branches to step  116  of  FIG. 6  when the processing module determines that the comparison is favorable. The method continues to step  114  of  FIG. 6  when the processing module determines that the comparison is not favorable. The method continues at step  114  of  FIG. 6  where the processing module indicates a failed test when the processing module determines that the sum of the compressed encoded data slice partials does not compare favorably to the selected compressed encoded data slice. In addition, the processing module may keep testing the same encoded data slice utilizing other permutations of the selected DS unit. The method continues at step  116  of  FIG. 6  where the processing module indicates a passed test when the processing module determines the comparison is favorable. 
       FIG. 8  is a flowchart illustrating an example of selecting dispersed storage (DS) units, which include similar steps to  FIG. 6 . A method begins with step  128  where a processing module (e.g., of a DS unit) determines a slice name of an encoded data slice to rebuild or verify. The determination may be based on one or more of a slice error indicator, an error message, a request, a next slice name in a list of slices to test, a random slice name, a slice name associated with a local DS unit, and a slice rebuild indicator. For example, the processing module determines the slice name based on a rebuild indicator subsequent to an encoded data slice being rebuilt. In such an example, the processing module determines to verify the encoded data slice associated with the slice name. The method continues at step  106  of  FIG. 6  where the processing module determines a storage set of DS units associated with the slice name. 
     The method continues at step  130  where the processing module determines a historical performance level of each DS unit of the storage set of DS units. The determination may be based on one or more of retrieving a historical performance level record, a query, a test, a lookup, and a message. Dimensions of such performance may include one or more of access latency, excess bandwidth, reliability, availability, and cost. The method continues at step  132  where the processing module determines an estimated performance level of each DS unit of the storage set of DS units. The determination may be based on one or more of the historical performance level of each DS unit, an estimation guideline, a query, a test, a lookup, and a message. For example, processing module determines the estimated performance level of DS unit  3  based on the historical performance level of DS unit  3  for the last  30  days and the estimation guideline indicating that future estimated performance may be determined as an average of historical performance levels for the last 30 days. 
     The method continues at step  134  where the processing module selects at least a decode threshold number of DS units of the storage set of DS units to produce selected DS units. The selection may be based on one or more of system topology information (e.g., sites, number of DS units per site, site locations, etc.), the historical performance level, the estimated performance level, a performance goal, and a selection approach indicator (e.g., select as many DS units co-located with a present DS unit as possible, select the issuance of a remote site with a maximum number of DS units). For example, the processing module selects all three DS units (e.g., DS units  2 - 4 ) co-located with a present DS unit  1  (e.g., where the encoded data slice is stored), all four DS units (e.g., DS units  5 - 8  located at a second site, and DS unit  9  located at a third site in accordance with the selection approach indicator when the decode threshold is  8  and all the selected DS units are included in the storage set of DS units. 
     The method continues at step  136  where the processing module determines an encoded data slice partial aggregation scheme for the selected DS units. The scheme may include which DS units compute their encoded data slice partial, which DS units aggregate their encoded data slice partial with encoded data slice partials from which other DS units to produce aggregated encoded data slice partials, and which DS units are to be recipients of the aggregated encoded data slice partials. The determination may be based on one or more of the selected DS units, the system topology information, a DS unit capability indicator, the historical performance level, the estimated performance level, a security goal, and a random issued selection per site. In a ring structure example, the processing module determines the encoded data slice partial aggregation scheme to include DS unit  9  sends its encoded data slice partial to DS unit  8 , DS unit  8  receives encoded data slice partials from local DS units  5 - 7 , &amp;  9  and aggregates the encoded data slice partials from DS units  5 - 9  to produce an aggregated encoded data slice partial, DS unit  8  sends the aggregated encoded data slice partial to DS unit  1 , DS unit  1  receives the aggregated encoded data slice partial from DS unit  8 , DS unit  1  receives encoded data slice partials from local DS units  2 - 4 , and DS unit  1  aggregates the encoded data slice partials from DS units  2 - 4  and the aggregated encoded data slice partial from DS unit  8  to produce the encoded data slice. In a star structure example, the processing module determines the encoded data slice partial aggregation scheme to include DS unit  9  sends its encoded data slice partial to DS unit  1 , DS unit  8  receives encoded data slice partials from local DS units  5 - 7  and aggregates the encoded data slice partials from DS units  5 - 8  to produce an aggregated encoded data slice partial, DS unit  8  sends the aggregated encoded data slice partial to DS unit  1 , DS unit  1  receives the aggregated encoded data slice partial from DS unit  8 , DS unit  1  receives encoded data slice partials from local DS units  2 - 4 , and DS unit  1  aggregates the encoded data slice partials from DS units  2 - 4 , &amp;  9  and the aggregated encoded data slice partial from DS unit  8  to produce the encoded data slice. 
     The method continues at step  138  where the processing module sends encoded data slice partial request messages to the selected DS units. The request messages may include one or more of the encoded data slice partial aggregation scheme, a slice name corresponding to an encoded data slice associated with the DS unit of associated with the request message, a recipient identifier (ID), and compression information (e.g., as previously discussed). The method continues at step  140  where the processing module receives encoded data slice partial response messages and extracts encoded data slice partials from the messages. Next, the processing module facilitates rebuilding or verifying the encoded data slice utilizing the encoded data slice partials. 
       FIG. 9A  is a flowchart illustrating an example of rebuilding an encoded data slice. A method begins with step  142  where a processing module (e.g., of a dispersed storage (DS) unit, of DS processing unit) identifies an encoded data slice to be rebuilt. The identification may be based on one or more of a slice error indicator, a missing slice indicator, a corrupted slice indicator, an error message, a request, a next slice name in a list of slices to test, a random slice name, a slice name associated with a local DS unit, detecting an error condition associated with the encoded data slice to be rebuilt, receiving a message, and a slice rebuild indicator. The method continues at step  144  where the processing module selects a decode threshold number of dispersed storage (DS) units of a storage set of DS units associated with the encoded data slice to be rebuilt (e.g., a set of encoded data slice is stored in the set of DS units that includes the encoded data slice to be rebuilt). The selecting may be based on one or more of a DS unit availability indicator, a DS unit capability indicator, and a DS unit performance level indicator. 
     The method continues at step  146  where the processing module generates a decode threshold number of key pairs, wherein a key pair of the decode threshold number of key pairs corresponds to a DS unit of the decode threshold number of DS units. The generating the decode threshold number of key pairs includes generating a decode threshold number of unique keys based on at least one of a random number generator, a random key generator, a predetermined key, a key seed, a key list, a private key, a public key, a received key, a slice name, a slice revision, a DS unit identifier, and a previous key and uniquely pairing keys of the decode threshold number of unique keys to produce the decode threshold number of key pairs. Each key of the decode threshold number of unique keys includes a number of bits substantially the same as a number of bits of the encoded data slice to be rebuilt. For example, the processing module may generate each key of the decode threshold number of unique keys to include the number of bits substantially the same as the number of bits of the encoded data slice to be rebuilt by expanding a random key to a length (e.g. number of bits) of the encoded data slice to produce an expanded key utilizing a stream cipher (e.g., Rivest cipher 4 (RC4)). As another example, the processing module expands the random key to the length of the encoded data slice to produce the expanded key utilizing a block cipher in counter mode to generate a pseudo-random stream of a length that matches the length of the encoded data slice. The unique pairing of the unique keys includes for each key pair of the decode threshold number of key pairs, selecting a first key and a second key from the decode threshold number of unique keys, wherein the second key is substantially different than the first key, and wherein the key pair is unique, and wherein each key of the decode threshold number of unique keys is selected an even number of times. 
     The method continues at step  148  where the processing module sends partial rebuilding requests to the decode threshold number of DS units, wherein a partial rebuilding request of the partial rebuilding requests includes one or more of the key pair, identity of the corresponding DS unit, a slice name of the encoded data slice to be rebuilt, a slice name corresponding to an encoded data slice associated with the DS unit, pillar identifiers of the decode threshold number of DS units (e.g., participating DS units), an encoding matrix, an inverted matrix, and a row of the encoding matrix corresponding to the encoded data slice to be rebuilt. Alternatively, the processing module sends the key pairs in separate messages. For example, the processing module generates three keys and generates key pairs as k 1  &amp; k 2  for partial A, k 1  &amp; k 3  for partial B, and k 2  &amp; k 3  for partial C when the decode threshold is three. As another example, the processing module generates four keys and generates key pairs as k 1  &amp; k 3  for partial A, k 1  &amp; k 4  for partial B, k 2  &amp; k 3  for partial C, and k 2  &amp; k 4  for partial D when the decode threshold is four. As yet another example, the processing module generates five keys and generates key pairs as k 1  &amp; k 3  for partial A, k 1  &amp; k 4  for partial B, k 2  &amp; k 5  for partial C, k 2  &amp; k 4  for partial D, and k 3  &amp; k 5  for partial E when the decode threshold is five. As a still further example, the processing module generates six keys and generates key pairs as k 1  &amp; k 4  for partial A, k 1  &amp; k 5  for partial B, k 2  &amp; k 4  for partial C, k 2  &amp; k 6  for partial D, k 3  &amp; k 5  for partial E, and k 3  &amp; k 6  for partial F when the decode threshold is six. 
     The method continues at step  150  where the processing module receives encrypted partial encoded data slices in response to the partial rebuilding requests, wherein an encrypted partial encoded data slice received from the corresponding DS unit includes a multiple encryption, using the key pair, of a partial encoded data slice. The partial encoded data slice includes a result of a partial encoded data slice generation function including obtaining an encoding matrix utilized to generate the encoded data slice to be rebuilt, reducing the encoding matrix to produce a square matrix that exclusively includes rows associated with the decode threshold number of DS units, inverting the square matrix to produce an inverted matrix, matrix multiplying the inverted matrix by an encoded data slice associated with the DS unit to produce a vector, and matrix multiplying the vector by a row of the encoding matrix corresponding to the encoded data slice to be rebuilt to produce the partial encoded data slice. 
     The method continues at step  152  where the processing module decodes the encrypted partial encoded data slices to rebuild the encoded data slice. The decoding the encrypted partial encoded data slices includes one of performing a logical exclusive OR function between each encrypted partial encoded data slice of the encrypted partial encoded data slices to rebuild the encoded data slice and performing the logical exclusive OR function between each encrypted partial encoded data slice and a corresponding key pair of the decode threshold number of key pairs to produce a decode threshold number of interim slices and performing the logical exclusive OR function between each interim slice of the decode threshold number of interim slices to reproduce the encoded data slice to be rebuilt. The exclusive OR function step will cancel out all the keys leaving the partial encoded data slices summed with each other to reproduce the encoded data slice to be rebuilt since the encrypted partial encoded data slices were previously encrypted with two keys utilized an even number of times (e.g., twice) across all the encrypted partial encoded slices. 
       FIG. 9B  is a flowchart illustrating an example of generating an encrypted partial encoded data slice. The method begins with step  154  where a processing model (e.g., of a participating dispersed storage (DS) unit, of a DS processing unit) receives a partial rebuilding request (e.g., from a requesting entity), wherein the request includes a key pair. Alternatively, the processing module generates the key pair utilizing a Diffie-Hellman key exchange protocol with the requesting entity. The method continues at step  156  where the processing module retrieves (e.g., utilizing a slice name of the request) an encoded data slice associated with the partial encoded data slice request. In addition, the processing module may generate a new key pair based on the key pair. For example, the processing module expands the key pair to be a same number of bits as the encoded slice to produce the new key pair. 
     The method continues at step  158  where the processing module generates a partial encoded data slice based on the request and the encoded data slice associated with the request. The generating the partial encoded data slice includes one or more of obtaining an encoding matrix utilized to generate the encoded data slice (e.g., extract from the partial rebuilding request, retrieve from a memory), reducing the encoding matrix to produce a square matrix that exclusively includes rows identified in the partial rebuilding request (e.g., slice pillars associated with participating DS units of a decode threshold number of DS units), inverting the square matrix to produce an inverted matrix (e.g. alternatively, may extract the inverted matrix from the partial rebuilding request), matrix multiplying the inverted matrix by the encoded data slice to produce a vector, and matrix multiplying the vector by a row of the encoding matrix corresponding to an encoded data slice to be rebuilt (e.g. alternatively, may extract the row from the partial rebuilding request), to produce the partial encoded data slice (e.g., encoded data slice to be rebuilt identified in the partial rebuilding request). 
     The method continues at step  160  where the processing module multiple encrypts the partial encoded data slice using the key pair to produce an encrypted partial encoded data slice. The multiple encrypting the partial encoded data slice includes encrypting the partial encoded data slice utilizing a first key of the key pair to produce an interim slice and encrypting the interim slice utilizing a second key of the key pair to produce the encrypted partial encoded data slice. The encrypting the partial encoded data slice utilizing the first key includes at least one of performing a logical exclusive OR function between the partial encoded data slice and the first key to produce the interim slice and encrypting the partial encoded data slice utilizing the first key to produce the interim slice. The encrypting the interim slice utilizing the second key includes at least one of performing a logical exclusive OR function between the interim slice and the second key to produce the encrypted partial encoded data slice and encrypting the interim slice utilizing the second key to produce the encrypted partial encoded data slice. The method continues at step  162  where the processing module outputs the encrypted partial encoded data slice. For example, the processing module sends the encrypted partial encoded data slice to the requesting entity. 
       FIG. 9C  is a block diagram of a rebuilding module  125  that operates in accordance with the method described in  FIG. 9A . The rebuilder module  125  is a module that includes one or more sub-modules, which include an identify module  127 , a select module  129 , a key pair generate module  131 , a send module  133 , a receive module  135 , and a decode module  137 . The select module  129  selects a decode threshold number of dispersed storage (DS) units  36  of a storage set of DS units of a dispersed storage network (DSN) memory  22  associated with the encoded data slice to be rebuilt to produce selected DS units  141 . 
     The key pair generate module  131  generates a decode threshold number of key pairs  143 , wherein a key pair of the decode threshold number of key pairs  143  corresponds to a DS unit of the decode threshold number of DS units  141 . The key pair generate module  131  generates the decode threshold number of key pairs  143  by generating a decode threshold number of unique keys based on at least one of a random number generator, a random key generator, a predetermined key, a key seed, a key list, a private key, and public key, a received key, and a previous key and uniquely pairing keys of the decode threshold number of unique keys to produce the decode threshold number of key pairs  143 . 
     The send module  133  sends partial rebuilding requests  145  to the decode threshold number of DS units  141 , wherein a partial rebuilding request of the partial rebuilding requests  145  includes the key pair and identity of the corresponding DS unit. The receive module  135  receives encrypted partial encoded data slices  147  in response to the partial rebuilding requests, wherein an encrypted partial encoded data slice received from the corresponding DS unit includes a multiple encryption, using the key pair, of a partial encoded data slice. 
     The decode module  137  decodes the encrypted partial encoded data slices  147  to rebuild the encoded data slice  149 . The decode module  137  decodes the encrypted partial encoded data slices  147  by one of performing a logical exclusive OR function between each encrypted partial encoded data slice of the encrypted partial encoded data slices to rebuild the encoded data slice and performing the logical exclusive OR function between each encrypted partial encoded data slice and a corresponding key pair of the decode threshold number of key pairs  143  to produce a decode threshold number of interim slices and performing the logical exclusive OR function between each interim slice of the decode threshold number of interim slices to reproduce the encoded data slice  149  to be rebuilt. 
       FIG. 9D  is a block diagram of another rebuilding module  161  that operates in accordance with the method described in  FIG. 9B . The rebuilder module  161  is a module that includes one or more sub-modules, which include a receive module  163 , a retrieve module  165 , a generate module  167 , an encrypt module  169 , and an output module  171 . The receive module  163  receives a partial rebuilding request  173  (e.g., from a requesting dispersed storage (DS) unit  36  of a dispersed storage network (DSN) memory  22 ) wherein the request includes a key pair  175 . The retrieve module  165  retrieves an encoded data slice  177  associated with the partial encoded data slice request  173 . 
     The generate module  167  generates a partial encoded data slice  179  based on the request  173  and the encoded data slice  177  associated with the request. The generate module  167  generates the partial encoded data slice  179  by one or more of obtaining an encoding matrix utilized to generate the encoded data slice, reducing the encoding matrix to produce a square matrix that exclusively includes rows identified in the partial rebuilding request, inverting the square matrix to produce an inverted matrix, matrix multiplying the inverted matrix by the encoded data slice to produce a vector, and matrix multiplying the vector by a row of the encoding matrix corresponding to an encoded data slice to be rebuilt to produce the partial encoded data slice  179 . 
     The encrypt module  169  multiple encrypts the partial encoded data slice  179  using the key pair  175  to produce an encrypted partial encoded data slice  181 . The encrypt module  169  multiple encrypts the partial encoded data slice  179  by encrypting the partial encoded data slice  179  utilizing a first key of the key pair  175  to produce an interim slice and encrypting the interim slice utilizing a second key of the key pair  175  to produce the encrypted partial encoded data slice  181 . Alternatively, the encrypt module  169  encrypts the partial encoded data slice  179  utilizing the first key by at least one of performing a logical exclusive OR function between the partial encoded data slice  179  and the first key to produce the interim slice and encrypting the partial encoded data slice  179  utilizing the first key to produce the interim slice. In addition, the encrypt module  169  may encrypt the interim slice utilizing the second key by at least one of performing a logical exclusive OR function between the interim slice and the second key to produce the encrypted partial encoded data slice  181  and encrypting the interim slice utilizing the second key to produce the encrypted partial encoded data slice  181 . The output module  171  out puts the encrypted partial encoded data slice (e.g., to the requesting DS unit  36 ). 
       FIG. 10A  is a flowchart illustrating another example of rebuilding an encoded data slice, which include similar steps to  FIG. 9A . The method begins with steps  142 - 148  of  FIG. 9A  where a processing module (e.g. of a dispersed storage (DS) unit initiating a star structure rebuilding process) identifies an encoded data slice to be rebuilt (e.g., identifies a slice name associated with the encoded data slice to be rebuilt), selects a decode threshold number of DS units of a storage set of DS units associated with the encoded data slice to be rebuilt to produce selected DS units and a participant list, and sends partial rebuilding requests to the decode threshold number of DS units. The participant list includes a list of DS unit identifiers (IDs) associated with the selected DS units. 
     The method continues at step  164  where the processing module determines public constants. The public constants may be subsequently utilized with an associated shared secret approach to determine a shared secret between two DS units. The shared secret approach may include one of a Shamir shared secret method and a Diffie-Hellman shared secret method. The public constants may include one or more of participant IDs, the participant list, a Diffie-Hellman constant g, and a Diffie-Hellman constant p. Note that g may be a small number like  2  or  5  and p may be a large prime number with hundreds of digits. 
     The method continues at step  166  where the processing module sends the public constants and the participant list to participants of the participant list. For example, the processing module sends the public constants and the participant list to each DS unit of the decode threshold number of DS units. The method continues at step  168  where the processing module determines a public value based on the public constants and a private constant. The private constant may include a large number with hundreds of digits. For example, the processing module generates the public value as y=g{circumflex over ( )}(private constant) mod p when utilizing the Diffie-Hellman shared secret method. 
     The method continues at step  170  where the processing module receives participant public values (e.g., public values created by each participant DS unit). The method continues at step  172  where the processing module sends the public value and the participant public values to the participants (e.g., utilizing the participants IDs of the participant list). For example, the processing module sends all of the public values to the selected DS units. 
     The method continues at step  174  where the processing module determines a shared secret set for the participants. In an example utilizing the Diffie-Hellman shared secret method, the processing module generates a shared secret as S=(participant public value){circumflex over ( )}(private constant) mod p. The processing module determines the shared secret set by calculating a shared secret for each pairing of a present DS unit and a DS unit of the participant list. 
     The method continues at step  176  where the processing module determines a key set based on the shared secret set and an associated slice name. For example, the processing module determines a key of the key set as key=hash based message authentication code (HMAC) of (the participant list +the participant public values+a recipient ID+an associated slice name) utilizing an associated shared secret as a HMAC key. The processing module may utilize finite field math to sum elements of the HMAC. For instance, the recipient ID corresponds to a DS unit ID of a participant DS unit responding to an initiating DS unit. As another instance, the recipient ID corresponds to a DS unit ID of the initiating DS unit. In an instance, the associated slice name corresponds to a slice name affiliated with the participant DS unit. As yet another instance, the associated slice name corresponds to the slice name (e.g., affiliated with the initiating DS unit). 
     The method continues at step  178  where the processing module determines a set of expanded keys based on the key set and a length of the encoded data slice. For example, the processing module expands a key to a length (e.g. number of bits) of the encoded data slice to produce an expanded key utilizing a stream cipher (e.g., Rivest cipher 4 (RC4)). As another example, the processing module expands the key to a length of the encoded data slice to produce the expanded key utilizing a block cipher in counter mode to generate a pseudo-random stream of a length that matches the length of the encoded data slice. 
     The method continues at step  180  where the processing module receives encrypted encoded data slice partial response messages that include encrypted encoded data slice partials. For example, the processing module receives the encrypted encoded data slice partial response messages from the selected DS units. The method continues at step  182  where the processing module decrypts the encoded data slice partials utilizing the set of expanded keys to produce the encoded data slice. For example, the processing module produces an encoded data slice=partial  1  XOR partial  2  XOR partial  3  etc. 
       FIG. 10B  is a flowchart illustrating an example of encrypting an encoded data slice partial, which includes similar steps to  FIGS. 9B and 10A . The method begins with step  184  where a processing module (e.g. of a participant dispersed storage (DS) unit participating in a star structure rebuilding process) receives an encrypted encoded data slice partial request message that includes a slice name (e.g., from an initiating DS unit). For instance, the slice name is associated with the participant DS unit (e.g., stored in the participant DS unit) and is affiliated with a slice name associated with the initiating DS unit wherein the encoded data slice associated with the slice name associated with the initiating DS unit is being rebuilt or verified. The method continues with step  158  of  FIG. 9B  where the processing module generates a partial encoded data slice based on the request and an encoded data slice associated with the request. 
     The method continues at step  186  where the processing module receives public constants and a participant list that includes participant identifiers (IDs). The method continues with step  168  of  FIG. 10A  where the processing module determines the public value based on the public constants and a private constant. The method continues at step  188  where the processing module sends the public value to participants (e.g., participating DS units) utilizing participants IDs of the participant list. For instance, the processing module sends the public value directly to the participants. As another instance, the processing module sends the public value to the initiating DS unit for publishing to the participants. The method continues with step  170  of  FIG. 10A  where the processing module receives participant public values. For example, the processing module receives the participant public values from the initiating DS unit. As another example, the processing module receives the participant public values from each of the participants (e.g., participating DS units). 
     The method continues at step  190  where the processing module determines a shared secret with at least one participant. For example, the processing module generates the shared secret as S=(participant public value){circumflex over ( )}(private constant) mod p when utilizing the Diffie-Hellman shared secret method. The processing module may utilize the initiating DS unit public value for the participant public value when the processing module determines a shared secret with the initiating DS unit. The processing module may utilize a participant public value associated with another participant (e.g., a different participating DS unit) when the processing module determines a shared secret with the other participant. Alternatively, or in addition to, the processing module determines a shared secret for each pairing of the participating DS unit with all other participants including the initiating DS unit. 
     The method continues at step  192  where the processing module determines a key based on a shared secret associated with the at least one participant and the slice name. The method continues at step  194  where the processing module determines an expanded key based on the key and the encoded data slice partial. The method continues at step  196  where the processing module encrypts the encoded data slice partial utilizing the expanded key to produce an encrypted encoded data slice partial. For example, the processing module determines the encrypted encoded data slice partial=(the encoded data slice partial) XOR (the expanded key). The method continues at step  198  where the processing module sends an encrypted encoded data slice partial response message that includes the encrypted encoded data slice partial. For example, the processing module sends the encrypted encoded data slice partial response message to the initiating DS unit. As another example, the processing module sends the encrypted encoded data slice partial response message to another participating DS unit. 
       FIG. 11A  is a flowchart illustrating another example of rebuilding an encoded data slice, which includes similar steps to  FIGS. 9A and 10A . The method begins with steps  142 - 148  of  FIG. 9A  where a processing module (e.g. of a dispersed storage (DS) unit initiating a ring structure rebuilding process) identifies an encoded data slice to be rebuilt (e.g., identifies a slice name associated with the encoded data slice), selects a decode threshold number of DS units (e.g., participating DS unit identifiers (IDs) of a participant list), and sends partial rebuilding requests to the decode threshold number of DS units (e.g., to request encrypted encoded data slice partials). 
     The method continues at step  200  where the processing module determines ring configuration information with reference to determining an encoded data slice partial aggregation scheme for a ring structure example. The method continues at step  202  where the processing module sends the ring configuration information to the selected DS units. The method continues with steps  174 - 176  of  FIG. 10A  where the processing module determines a shared secret set for the participant DS units and determines a key set based on the shared secret set. Each key of the key set may include an expanded key to match a length of the encoded data slice. 
     The method continues at step  204  where the processing module receives an aggregated encrypted encoded data slice partial response message that includes an aggregated encrypted encoded data slice partial. For example, the processing module receives one aggregated encrypted encoded data slice partial response message that includes an encrypted encoded data slice as the aggregated encrypted encoded data slice partial. The method continues at step  206  where the processing module decrypts the aggregated encrypted encoded data slice partial utilizing the key set to reproduce the encoded data slice to be rebuilt. For example, the processing module produces the encoded data slice=(aggregated encrypted encoded data slice partial) XOR key  1  XOR key  2  XOR key  3  etc. for all the keys. 
       FIG. 11B  is a flowchart illustrating another example of encrypting an encoded data slice partial, that includes similar steps to  FIGS. 9B and 10B . The method begins with step  184  of  FIG. 10B  where a processing module (e.g. of a participating dispersed storage (DS) unit participating a ring structure rebuilding process) receives an encrypted encoded data slice partial request message that includes a slice name. The method continues at step  208  where the processing module receives (e.g., from an initiating DS unit) ring configuration information. The method continues with step  158  of  FIG. 9B  where the processing module generates an encoded data slice partial of an encoded data slice associated with the slice name. The method continues with steps  190 - 192  of  FIG. 10B  where the processing module determines a shared secret with an initiator (e.g., the initiating DS unit) and determines a key based on the shared secret. 
     The method continues at step  210  where the processing module encrypts the encoded data slice partial utilizing the key to produce an encrypted encoded data slice partial. For example, the processing module produces the encrypted encoded data slice partial=(the encoded data slice partial) XOR (the key). 
     The method continues at step  212  where the processing module determines whether to receive an upstream encrypted encoded data slice partial. The upstream encrypted encoded data slice partial may include an encrypted encoded data slice from a sending DS unit (e.g., upstream with respect to a ring structure of the ring configuration information). The determination may be based on the ring configuration information. For example, the processing module determines not to receive the upstream encoded data slice partial when the ring configuration information indicates that the participating DS unit is a first DS unit of the ring structure. The method branches to step  216  when the processing module determines to receive the upstream encrypted encoded data slice partial. The method continues to step  214  when the processing module determines to not receive the upstream encrypted encoded data slice partial. The method continues at step  214  where the processing module sends an aggregated encrypted encoded data slice partial response message that includes the encrypted encoded data slice partial in accordance with the ring configuration information (e.g., the processing module sends the message to a downstream DS unit with respect to the ring structure). 
     The method continues at step  216  where the processing module receives (e.g., from the upstream DS unit with respect to the ring structure) the upstream encrypted encoded data slice partial when the processing module determines to receive the upstream encrypted encoded data slice partial in accordance with the ring configuration information. The method continues at step  218  where the processing module aggregates the encrypted encoded data slice partial with the upstream encrypted encoded data slice partial to produce an aggregated encrypted encoded data slice partial. For example, the processing module produces the aggregated encrypted encoded data slice partial=(the encrypted encoded data slice partial) XOR (the upstream encrypted encoded data slice partial). 
     The method continues at step  220  where the processing module sends the aggregated encrypted encoded data slice partial response message that includes the aggregated encrypted encoded data slice partial in accordance with the ring configuration information. For example, the processing module sends the aggregated encrypted encoded data slice partial response message to a downstream DS unit with respect to the ring structure. 
       FIG. 12A  is a flowchart illustrating an example of assigning storage resources. The method begins with step  222  where a processing module (e.g., of a dispersed storage (DS) managing unit) determines an addressing range of a storage configuration. The addressing range may include a virtual dispersed storage network (DSN) address range (e.g., a from address, a to address, a number of addresses in the range). The storage configuration may include one or more DS units assigned to the addressing range. For example, two DS units store the same encoded data slices when the two DS units are assigned to the same addressing range. The determination may be based on one or more of a next address range in a list of address ranges to be tested, an error message, a performance indicator, and a system capacity indicator. For example, the processing module determines an addressing range X when receiving a performance indicator that indicates an issue with storage within addressing range X. 
     The method continues at step  224  where the processing module determines a storage performance level associated with the addressing range. The storage performance level may include one or more of a read latency time, a write latency time, a read data rate, a write data rate, an availability indicator, and a reliability indicator. The determination may be based on one or more of a query, a test, a lookup, retrieval of a historical record, and a message. 
     The method continues at step  226  where the processing module determines whether the storage performance level compares favorably to a storage performance threshold. For example, the processing module determines that the storage performance level compares favorably to the storage performance threshold when the storage performance level is not over performing or underperforming. The method repeats back to step  222  when the processing module determines that the storage performance level compares favorably to the storage performance threshold. In such a scenario, the processing module may determine a different address range to test. The method continues to step  228  when the processing module determines that the storage performance level compares unfavorably to the storage performance threshold. 
     The method continues at step  228  where the processing module determines an updated storage configuration associated with the addressing range. For example, the processing module removes DS units from the addressing range when the storage performance level indicates over performing. For instance, the processing module detects over performing when a read data rate is higher than a threshold data rate. As another example, the processing module adds DS units to the addressing range when the storage performance level indicates underperforming. For instance, the processing module detects underperforming when the read data rate is lower than a threshold data rate. The processing module may select DS units in accordance with a selecting method. Such a selecting method is discussed in greater detail with reference to  FIG. 12B . 
     The method continues at step  230  where the processing module re-assigns storage resources in accordance with the updated storage configuration. For example, the processing module updates a virtual DSN address to physical location table to include DS units assigned to the addressing range. As another example, the processing module sends an addressing range assignment message to the DS units assigned to the addressing range. As yet another example, the processing module sends an addressing range de-assignment message to the issuance no longer assigned to the addressing range. The method repeats back to step  222  to potentially analyze a still further addressing range. 
       FIG. 12B  is a flowchart illustrating an example of selecting storage resources. The method begins with step  232  where a processing module (e.g., of a dispersed storage (DS) processing unit) receives a slice retrieval request including a slice name. The processing module may receive the slice retrieval request as a result of a data retrieval request. The method continues at step  234  where the processing module determines a storage configuration associated with the slice name. The storage configuration includes a list of which DS units are assigned to a common slice name (e.g., same addressing range). The determination may be based on one or more of a storage configuration lookup, a virtual dispersed storage network (DSN) to physical location table lookup, a query, a message, and a predetermination. 
     The method continues at step  236  where the processing module determines an estimated performance level for each storage resource of storage resources associated with the slice name based on the storage configuration. The performance level for each storage resource may include one or more of an access latency time, a read data rate, a write data rate, an availability indicator, and a reliability indicator. The determination may be based on one or more of a performance history record, a storage configuration lookup, a query, a message, a predetermination, and information in a retrieval message. 
     The method continues at step  238  where the processing module determines a retrieval performance goal. The retrieval performance goal may include one or more of a latency time, a read data rate, a write data rate, an availability level, and a reliability level. The determination may be based on one or more of a storage configuration lookup, a query, a message, a predetermination, and information retrieved in a retrieval message. 
     The method continues at step  240  where the processing module selects a storage resource of the storage resources to produce a selected storage resource. The selection may be based on one or more of the estimated performance levels, the retrieval performance goal, and the storage configuration. For example, the processing module selects a DS unit with an estimated performance level compares favorably (e.g., superior) to the retrieval performance goal. The method continues at step  242  where the processing module sends a read request message to the selected storage resource that includes the slice name. 
       FIG. 13A  is a flowchart illustrating an example of storing an encoded data slice. The method begins with step  244  where a processing module (e.g., of a dispersed storage (DS) processing unit) receives a slice storage request that includes an encoded data slice. For example, the processing module receives the slice storage request as a result of a data storage sequence. The method continues at step  246  where the processing module determines whether an associated DS unit is available. The determination may be based on one or more of a virtual dispersed storage network (DSN) address to physical location table lookup (e.g., indicating which DS unit is associated with the encoded data slice based on a slice name), a query, a message, a performance indicator, an available memory indicator. For example, the processing module determines that DS unit  6  is associated with the encoded data slice based on the virtual DSN address to physical location table lookup and that DS unit  6  is presently available based on an available memory indicator associated with DS unit  6 . The method branches to step  250  when the processing module determines that the associated DS unit is not available. The method continues to step  248  when the processing module determines that the associated DS unit is available. The method continues at step  248  where the processing module sends a write request message to the associated DS unit that includes the encoded data slice. 
     The method continues at step  250  where the processing module encrypts the encoded data slice utilizing a random key to produce an encrypted encoded data slice when the processing module determines that the associated DS unit is not available. The processing module may produce the random key based on a random number generator. The method continues at step  252  where the processing module encrypts the random key utilizing a key associated with the associated DS unit to produce an encrypted random key. For example, the processing module encrypts the random key utilizing a public key of a public-key infrastructure (PKI) encryption approach associated with the associated DS unit to produce the encrypted random key. 
     The method continues at step  254  where the processing module determines an available foster DS unit. The foster DS unit may temporarily store slices on behalf of the DS unit that is not available. The determination may be based on one or more of a foster DS unit list, a query, a message, a performance indicator, and an available memory indicator. For example, the processing module determines that DS unit  6  is the available foster DS unit when the processing module determines that the DS unit  6  is listed in the foster DS unit list and an available memory indicator associated with DS unit  6  indicates that DS unit  6  is available. 
     The method continues at step  256  where the processing module sends a write request messages to the foster DS unit that includes a signed package wherein the signed package includes the encrypted encoded data slice, the encrypted random key, and a signature over the encrypted encoded data slice and the encrypted random key. The foster DS unit may subsequently send the signed package to the associated DS unit when the associated DS unit is once again available to facilitate storing the encoded data slice in the associated DS unit. 
       FIG. 13B  is a flowchart illustrating another example of storing an encoded data slice. The method begins with a processing module (e.g., of an associated dispersed storage (DS) unit associated with an encoded data slice temporarily stored in a foster DS unit) receives a store slice request message that includes a signed package including one or more of an encrypted encoded data slice, an encrypted random key, and a signature over the encrypted encoded data slice and the encrypted random key. The method continues at step  260  where the processing module determines whether the signature is valid. For example, the processing module compares a calculated hash over the encrypted encoded data slice and the encrypted random key to a decrypted signature utilizing a private key associated with the associated DS unit. For instance, the processing module validates the signature when the processing module determines that the calculated hash over the encrypted encoded data slice and the encrypted random key is substantially the same as the decrypted signature. The method branches to step  264  when the processing module determines that the signature is valid. The method continues to step  262  when the processing module determines that the signature is not valid. The method continues at step  262  where the processing module rejects the package. For example, the processing module sends an error message to a requesting entity to reject the package. 
     The method continues at step  264  where the processing module determines whether the request is authorized when the processing module determines that the signature is valid. The determination may be based on one or more of an access control list (ACL) query, a user device identifier (ID), a DS processing unit ID, a vault ID, a source name, a slice name, and a data object ID. For example, the processing module determines that the request is authorized when the processing module determines that a user ID associated with the request is identified in the ACL as authorized to access the encoded data slice associated with a slice name of the request. The method branches to step  266  when the processing module determines that the request is authorized. The method continues to step  262  to reject the package when the processing module determines that the request is not authorized. 
     The method continues at step  266  where the processing module decrypts the encrypted random key to produce a random key. For example, the processing module decrypts the encrypted random key utilizing a private key associated with a private key infrastructure (PKI) encryption approach associated with the associated DS unit to produce the random key. The method continues at step  268  where the processing module decrypts the encrypted encoded data slice utilizing the random key to produce an encoded data slice. The method continues at step  270  where the processing module stores the encoded data slice. For example, the processing module stores the encoded data slice in a memory of the associated DS unit. Alternatively, or in addition to, the processing module may store the signed package in a memory of the associated DS unit wherein the encrypted encoded data slice and the encrypted random key may be subsequently retrieved enabling subsequent decrypting of the encrypted encoded data slice to produce the encoded data slice. In such a scenario, a security improvement may be provided. 
       FIG. 14A  is a schematic block diagram of another embodiment of a computing system. The system includes a user device  12 , a plurality of dispersed storage (DS) processing units  1 -N, a plurality of dispersed storage network (DSN) memories  1 -N that each include a plurality of DS units  1 -n. Alternatively, a plurality of DS processing modules and/or DS modules may be utilized to implement the plurality of DS processing units  1 -N. Alternatively, the plurality of DSN memories  1 -N may be implemented with one DSN memory. Each DSN memory of the plurality of DSN memories  1 -N may include a different number of DS units when more than one DSN memory is utilized. 
     In an example of operation, the user device  12  sends data  280  to DS processing unit  1  for storage in the plurality of DSN memories  1 -N. DS processing unit  1  receives the data  280  and partitions the data  280  into a first portion and a second portion in accordance with a data partitioning dispersed storage scheme (e.g., including segmentation approach). For instance, DS processing unit  1  partitions the data such that the first portion and the second portion overlap wherein the first portion and the second portion share a common section. As another instance, DS processing unit  1  partitions the data into N data segments that includes a data segment  1  as the first portion and data segments  2 -N as the second portion. As yet another instance, DS processing unit  1  partitions the data into two data segments that includes data segment  1  as the first portion and data segment  2  as the second portion wherein data segment  1  and data segment  2  do not overlap. Next, DS processing unit  1  encodes (e.g., manipulates) the first portion (e.g. data segment  1 ) to create local data (e.g., first manipulated data) and sends the local data to DSN memory  1  for storage therein as is further discussed with reference to  FIGS. 14A-17F . Next, DS processing unit  1  sends the second portion to DS processing unit  2 . 
     In the example of operation continued, DS processing unit  2  receives the second portion and partitions the second portion into a third portion and a fourth portion in accordance with the data partitioning dispersed storage scheme. For instance, DS processing unit  2  partitions the second data portion such that the third portion and the fourth portion overlap wherein the third portion and the fourth portion share a common section. As another instance, DS processing unit  2  partitions the second portion into N- 1  data segments  2 -N that includes a data segment  2  as the third portion and data segments  3 -N as the fourth portion. As yet another instance, DS processing unit  2  segments the second portion into two data segments that includes data segment  2  as the third portion and data segment  3  as the fourth portion wherein data segment  2  and data segment  3  do not overlap. As a still further instance, DS processing unit  2  receives the second portion as data segments  2 -N that include data segment  2  as the third portion and data segments  3 -N as the fourth portion. Next, DS processing unit  2  encodes (e.g., manipulates) the third portion (e.g. data segment  2 ) to create second manipulated data and sends the second manipulated data to DSN memory  2  for storage therein as is further discussed with reference to  FIGS. 14A-17F . Next, DS processing unit  2  sends the fourth portion to DS processing unit  3 . Note that DS processing units  3 -(N- 1 ) may operate in accordance with the method described for DS processing unit  2 . In the example of operation continued, DS processing unit N receives data segment N from DS processing unit N- 1 . Next, DS processing unit N manipulates data segment N to create Nth manipulated data and sends the Nth manipulated data to DSN memory N for storage therein as is further discussed with reference to  FIGS. 14A-17F . 
     Each DS processing unit of the plurality of DS processing units  1 -N manipulates (e.g., encodes) a corresponding data segment to create corresponding manipulated data in accordance with a data manipulation approach. For example, DS processing unit  1  manipulates data segment  1  to create first manipulated data. As another example, DS processing unit  4  manipulates data segment  4  to create fourth manipulated data. The data manipulation approach may include encoding the data segment to create one or more of a section of a data segment, a data segment, a replicated data segment, an encoded data slice, and a plurality of encoded data slices. 
     Next, the DS processing unit sends the manipulated data to one or more DS units of a corresponding DSN memory in accordance with the data manipulation approach. For example, DS processing unit  1  sends a pillar width number of encoded data slices to the pillar width number of corresponding DS units of DSN memory  1 . For instance, DS processing unit  1  sends a first slice to DS unit  1 , a second slice to DS unit  2 , up through an nth slice to DS unit n. As another example, DS processing unit  1  sends data segment  1  to each of the pillar width number of DS units (e.g., DS units  1 -n) of DSN memory  1 . As yet another example, DS processing unit  1  sends a decode threshold number of sections (e.g., sections  1 -k) of data segment  1  to a corresponding decode threshold number of DS units (e.g., DS units  1 -k) of DSN memory  1 . As a still further example, DS processing unit  1  sends data segment  1  to a decode threshold number of DS units (e.g., DS units  1 -k) of DSN memory  1 . The pillar width n may vary from DS processing unit to DS processing unit in accordance with the data manipulation approach. For example, DS processing unit  2  may utilize a pillar width of  5  when DS processing unit  1  utilizes a pillar width of  16 . The decode threshold k may vary from DS processing unit to DS processing unit in accordance with the data manipulation approach. For example, DS processing unit  2  may utilize a decode threshold of  3  when DS processing unit  1  utilizes a decode threshold of  10 . 
     A DS processing unit and/or a DS unit may update a directory and/or a location table subsequent to storing the data in the plurality of DSN memories. For example, DS processing unit N updates a virtual DSN address to physical location table subsequent to confirming that data segment N has been successfully stored in DSN memory N. As another example, DS unit n of DSN memory N updates the virtual DSN address to physical location table subsequent to confirming that data segment N has been successfully stored in DSN memory N. The method of operation of each of the plurality of DS processing units is described in greater detail with reference to  FIGS. 14B-17F . The method of operation of each of the DS units of the plurality of DS units is described in greater detail with reference to  FIGS. 15C, 16E, and 17E -F. The method of operation of each of the plurality of DS processing units when the data manipulation approach indicates to send manipulated data as the pillar width number of encoded data slices to the pillar width number of DS units of the DSN memory is described in greater detail with reference to  FIG. 14B . 
     In a data retrieval example of operation, each DS processing unit retrieves manipulated data from a corresponding DSN memory in accordance with the data manipulation approach, decodes the manipulated data to produce a corresponding data segment in accordance with the data manipulation approach, sends the data segment to at least one other DS processing unit in accordance with the data segmentation approach, and aggregates data segments to reproduce the data in accordance with the data segmentation approach. 
       FIG. 14B  is a flowchart illustrating an example of storing data. The method begins with step  282  where a processing module (e.g., of a dispersed storage (DS) module) receives (e.g., from a user device, from a DS processing module, from a DS processing unit, from a DS unit) data for storage. The data may include one or more of at least a portion of a data object, at least a portion of a data block, a plurality of data blocks, and one or more data segments. The receiving the data includes receiving the data from a second other DS module and receiving a data partitioning dispersed storage scheme from the second other DS module. 
     Alternatively, the processing module may determine the data partitioning dispersed storage scheme based on one or more of a memory availability indicator, a data size indicator, a stored portion indicator, a redundancy indicator, a predetermination, and a lookup. The data partitioning dispersed storage scheme may include one or more storage indicators including a first portion and a second portion are to be adjacent, the first portion is to be embedded in the second portion, the second portion is to be embedded in the first portion, the first portion and the second portion overlap, the first portion in the second portion do not overlap, the first portion in the second portion are to be the same size, the first portion is to be smaller than the second portion, the second portion is to be smaller than the first portion, and the second portion is to be zero bytes. In addition, the processing module may receive metadata associated with the data, wherein the metadata includes one or more of a data identifier (ID), a user device ID, a vault ID, a source name, a stored portion indicator, a data size indicator, a data type indicator, a priority indicator, a security indicator, and a performance indicator. 
     The method continues at step  284  where the processing module determines whether to partition the data in accordance with the data partitioning dispersed storage scheme. The determining whether to partition the data includes interpreting data size of the data, determining whether the data size is of a level that requires partitioning in accordance with the data partitioning dispersed storage scheme, and when the data size is of a level that requires partitioning, indicating partitioning of the data. For example, the processing module determines to partition the data when the data size is 1 megabyte (MB) and the level that requires partitioning is 0.5 MB. The method branches to step  288  when the processing module determines to partition the data. The method continues to step  286  when the processing module determines not to partition the data. The method continues at step  286  where the processing module facilitates storing the data. The facilitating includes one or more of sending the data to a dispersed storage network (DSN) memory for storage therein, dispersed storage encoding the data to produce a plurality of local encoded data elements in accordance with dispersed storage encoding parameters and sending the plurality of local encoded data elements to the DSN memory for storage therein, and sending the data to another DS module. 
     The method continues at step  288  where the processing module partitions the data into a local data portion and a remaining data portion in accordance with the data partitioning dispersed storage scheme when the data is to be partitioned. The partitioning includes at least one of selecting a portion of the data per a data portion size indication of the data partitioning dispersed storage scheme to produce the local data portion and selecting the local data portion to have a partial overlap of data with the remaining data portion in accordance with the data partitioning dispersed storage scheme. 
     The method continues at step  290  where the processing module dispersed storage encodes the local data portion to produce a plurality of local encoded data elements in accordance with dispersed storage encoding parameters (e.g., associated with the data partitioning dispersed storage scheme). The dispersed storage encoding includes one or more of dispersed storage error encoding (e.g., to produce a plurality of encoded data slices), slicing the local data portion into a set of slices and encrypting the set of slices (e.g., such slices may be different sizes), slicing the local data portion into a set of slices, and replicating the local data portion. 
     The method continues at step  292  where the processing module sends the plurality of local encoded data elements to an associated dispersed storage network (DSN) memory for storage therein. The method continues at step  294  where the processing module sends the remaining data portion to another DS module. The sending the remaining data portion to another DS module includes selecting the other DS module based at least one of: the data partitioning dispersed storage scheme, a lookup, a query, and a message. For example, the processing module selects the DS module (e.g., a first DS module in a chain of DS modules) as the other DS module when the data partitioning dispersed storage scheme includes an iterative indicator. As another example, a processing module selects a previous DS module (e.g., source of the data) as the other DS module when the data partitioning dispersed storage scheme includes a previous DS module indicator. The method continues at step  296  where the processing module updates a location table to indicate storage of the local data portion within the associated DSN memory. 
       FIG. 14C  is a block diagram of a storing module  201  that operates in accordance with the method described in  FIG. 14B . The storing module  201  includes a receive module  203 , a partition data determination module  205 , a data partitioning module  207 , and a location table update module  209 . Alternatively, a single module (e.g., a dispersed storage (DS) module) may be implemented to provide functionality of modules  203 - 209 . The receive module  203  facilitates receiving data  211  and data partitioning dispersed storage scheme from a second other DS module (e.g., from a DS processing unit  16 ). The partition data determination module  205  determines whether to partition data  2111  in accordance with the data partitioning dispersed storage scheme, wherein the data is received for storage. The partition data determination module  205  determines whether to partition the data by interpreting data size of the data, determining whether the data size is of a level that requires partitioning in accordance with the data partitioning dispersed storage scheme, and when the data size is of a level that requires partitioning, indicating partitioning of the data. 
     When the data is to be partitioned, the data partitioning module  207  partitions the data into a local data portion and a remaining data portion  215  in accordance with the data partitioning dispersed storage scheme. The data partitioning module  207  partitions the data by selecting a portion of the data per a data portion size indication of the data partitioning dispersed storage scheme to produce the local data portion. The data partitioning module  207  may partition the data by selecting the local data portion to have a partial overlap of data with the remaining data portion  215  in accordance with the data partitioning dispersed storage scheme. 
     The data partitioning module  207  dispersed storage encodes the local data portion to produce a plurality of local encoded data elements  213  in accordance with dispersed storage encoding parameters. The dispersed storage encoding includes one or more of dispersed storage error encoding, slicing the local data portion into a set of slices and encrypting the set of slices, slicing the local data portion into a set of slices, and replicating the local data portion. 
     The data partitioning module  207  sends the plurality of local encoded data elements  213  to an associated dispersed storage network (DSN) memory  22  for storage therein and sends the remaining data portion  215  to another DS module (e.g., a DS processing unit). The data partitioning module  207  sends the remaining data portion  215  to the another DS module by selecting the other DS module based at least one of the data partitioning dispersed storage scheme, a lookup, a query, and a message. The location table update module  209  updates a location table  219  to indicate a storage of the local data portion within the associated DSN memory  22 . 
       FIG. 15A  is a schematic block diagram of another embodiment of a computing system. The system includes a user device  12 , a plurality of dispersed storage (DS) processing units  1 -N, a plurality of dispersed storage network (DSN) memories  1 -N that each includes a plurality of DS units  1 -n. Alternatively, a plurality of DS processing modules and/or DS modules may be utilized to implement the plurality of DS processing units  1 -N. Alternatively, the plurality of DSN memories  1 -N may be implemented with one DSN memory. Each DSN memory of the plurality of DSN memories  1 -N may include a different number of DS units when more than one DSN memory is utilized. 
     In an example of operation, the user device  12  sends data  280  to DS processing unit  1  for storage in the plurality of DSN memories. DS processing unit  1  receives the data  280  and partitions the data  280  into a first portion and a second portion in accordance with a segmentation approach. DS processing unit  1  manipulates the first portion (e.g. data segment  1 ) to create first manipulated data and sends the first manipulated data to DSN memory  1  for storage therein. Next, DS processing unit  1  sends the second portion to DS processing unit  2 . DS processing unit  2  receives the second portion and partitions the second portion into a third portion and a fourth portion in accordance with the segmentation approach. Next, DS processing unit  2  manipulates the third portion (e.g. data segment  2 ) to create second manipulated data and sends the second manipulated data to DSN memory  2  for storage therein. Next, DS processing unit  2  sends the fourth portion to DS processing unit  3 . DS processing units  3 -(N- 1 ) may operate in accordance with the method described for DS processing unit  2 . In the example of operation continued, DS processing unit N receives data segment N from DS processing unit N- 1 . Next, DS processing unit N manipulates data segment N to create Nth manipulated data and sends the Nth manipulated data to DSN memory N for storage therein. 
     Each DS processing unit of the plurality of DS processing units manipulates a corresponding data segment to create corresponding manipulated data in accordance with a data manipulation approach. Next, the DS processing unit sends the manipulated data to one or more DS units of a corresponding DSN memory in accordance with the data manipulation approach. For example, DS processing unit  1  sends data segment  1  to each of the pillar width number of DS units (e.g., DS units  1 -n) of DSN memory  1 . The DS processing unit and/or a DS unit may update a directory and/or location table subsequent to storing the data in the plurality of DSN memories. The method of operation of each of the plurality of DS processing units when the data manipulation approach indicates to send a data segment to each of the pillar width number of DS units of the DSN memory is described in greater detail with reference to  FIG. 15B . The method of operation of each of the DS units of the plurality of DS units when the data manipulation approach indicates to send the data segment to each of the pillar width number of DS units of the DSN memory is described in greater detail with reference to  FIG. 15C . 
     In a data retrieval example of operation, each DS processing unit retrieves manipulated data from a corresponding DSN memory in accordance with the data manipulation approach, decodes the manipulated data to produce a corresponding data segment in accordance with the data manipulation approach, sends the data segment to at least one other DS processing unit in accordance with a data segmentation approach, and aggregates data segments to produce the data in accordance with the data segmentation approach. 
       FIG. 15B  is a flowchart illustrating another example of storing data. A method begins with step  300  where a processing module (e.g., of a dispersed storage (DS) processing unit) receives (e.g., from a user device, from a DS processing unit, from a DS unit) a data storage request message that includes upstream data. The upstream data may include one or more of a data object, a data block, data, and one or more data segments of data. The data storage request message may include one or more of a data identifier (ID), the upstream data, a user device ID, a vault ID, a source name, a stored portion indicator, a data size indicator, a data type indicator, a priority indicator, a security indicator, and a performance indicator. 
     The method continues at step  302  where the processing module determines a storage portion of the upstream data. The determination may be based on one or more of a segmentation approach, a memory availability indicator, a memory availability threshold, the data size indicator, the stored portion indicator, a redundancy indicator, a predetermination, and a lookup. For example, the processing module determines the storage portion to be  1  megabyte (MB) when the memory availability indicator is greater than the memory availability threshold and the segmentation approach indicates to determine the storage portion to be  1  MB. 
     The method continues at step three for where the processing module determines whether to form downstream data based on the storage portion and the upstream data. The determination may be based on one or more of the data size indicator, a stored portion indicator, the storage portion. For example, the processing module determines not to form downstream data when a size of the storage portion is greater than or equal to a size of the upstream data. As another example, the processing module determines to form downstream data when the size of the storage portion is less than the size of the upstream data. The method branches to step  312  when the processing module determines not to form downstream data. The method continues to step  306  when the processing module determines to form downstream data. 
     The method continues at step  306  where the processing module determines downstream data based on the storage portion and the upstream data. The determination may be based on one or more of the storage portion, the upstream data, the stored portion indicator, and a redundancy indicator. For example, the processing module determines the downstream data to be the upstream data minus the storage portion when the redundancy indicator indicates no redundancy. As another example, the processing module determines the downstream data to be the upstream data minus the storage portion plus at least some of the storage portion. The method continues at step  308  where the processing module determines a recipient to receive the downstream data. The determination may be based on one or more of the segmentation approach, a list, a query, and the message. For example, processing module determines the recipient to be DS unit  3  when the processing modules associated with DS unit  2 . The method continues at step  310  where the processing module sends the downstream data to the recipient. 
     The method continues at step  312  where the processing module determines a DS unit storage set, where the DS unit storage set includes a pillar width number (e.g., n) of DS units. The determination may be based on one or more of the data manipulation approach, a list, a query, a message, a DS unit capability indicator, a DS unit availability indicator, a network traffic indicator, a list, and a predetermination. For example, the processing module determines to utilize DS units that are capable of dispersed storage error encoding the data segment to produce at least one encoded data slice based on the DS unit capability indicator. 
     The method continues at step  314  where the processing module sends a pillar width number of write request messages to DS units of the DS unit storage set that includes the storage portion (e.g., a data segment corresponding to the processing module). For example, the processing module sends a data segment  1  to each DS unit of DS units  1 -n. In addition, the processing module may update directory information and/or a data location table indicating storage locations associated with the data. 
       FIG. 15C  is a flowchart illustrating another example of storing an encoded data slice. The method begins step  316  where a processing module (e.g., a dispersed storage (DS) unit) receives a write request message that includes a storage portion (e.g., a data segment). The storage portion may include one or more of a data object, a data block, data, and one or more data segments of data. For example, the processing module receives the write request message that includes a data segment. The data storage request message may include one or more of a data identifier (ID), the storage portion, a user device ID, a vault ID, a DS processing unit ID, error coding dispersal storage function parameters, pillar selection information, a data manipulation approach, a source name, a stored portion indicator, a data size indicator, a data type indicator, a priority indicator, a security indicator, and a performance indicator. 
     The method continues at step  318  where the processing module determines pillar selection information. The pillar selection information may include pillar IDs of one or more pillars associated with the processing module such that the processing module stores or more slices encoded from the storage portion. The determination may be based on one or more of pillar selection information received in the write request message, a performance indicator, and available memory indicator, the storage portion, a predetermination, and a list. For example, the processing module determines the pillar selection information to include pillar  3  when the processing module is associated with DS unit  3  such that encoded at a slices of pillar  3  are typically stored in DS unit  3 . 
     The method continues at step  320  where the processing module dispersed storage error encodes the storage portion to produce a set of encoded data slices in accordance with error coding dispersal storage function parameters. For example, the processing module multiplies an encoding matrix times the data portion to produce the set of encoded data slices. For instance, processing module utilizes an encoding matrix that includes a pillar width number of rows. As another instance, the processing module utilizes an encoding matrix that includes only one row corresponding to a slice number associated with the processing module in accordance with the pillar selection information. In an example of such an instance, the processing module utilizes an encoding matrix that includes row  3  when the processing module determines that the pillar selection information indicates a pillar  3  assignment (e.g., encoded data slice  3 ). 
     The method continues at step  322  where the processing module selects one or more encoded data slices of the set of encoded data slices to produce selected encoded data slices based on the pillar selection information. For example, the processing module selects encoded data slice  3  when the pillar selection information includes selecting pillar  3 . 
     The method continues at step  324  where the processing module stores the selected encoded data slices. For example, the processing module stores the selected encoded data slices in a memory associated with the processing module (e.g., within a DS unit associated with the processing module). For instance, the processing module stores encoded data slice  3  in a local memory of DS unit  3 . As another example, the processing module stores the selected encoded data slice in another DS unit by sending a write request message to the another DS unit that includes the selected encoded data slice. The method continues at step  326  where the processing module updates directory information and/or a location table. 
       FIG. 16A  is a schematic block diagram of another embodiment of a computing system. The system includes a user device  12 , a plurality of dispersed storage (DS) processing units  1 -N, a plurality of dispersed storage network (DSN) memories  1 -N that each include a plurality of DS units  1 -n. Alternatively, a plurality of DS processing modules and/or DS modules may be utilized to implement the plurality of DS processing units  1 -N. Alternatively, the plurality of DSN memories  1 -N may be implemented with one DSN memory. Each DSN memory of the plurality of DSN memories  1 -N may include a different number of DS units when more than one DSN memory is utilized. 
     In an example of operation, the user device  12  sends data  28  to DS processing unit  1  for storage in the plurality of DSN memories. DS processing unit  1  receives the data  280  and partitions the data  280  into a first portion and a second portion in accordance with a segmentation approach. Next, DS processing unit  1  manipulates the first portion (e.g. data segment  1 ) to create first manipulated data and sends the first manipulated data to DSN memory  1  for storage therein. Next, DS processing unit  1  sends the second portion to DS processing unit  2 . DS processing unit  2  receives the second portion and partitions the second portion into a third portion and a fourth portion in accordance with the segmentation approach. Next, DS processing unit  2  manipulates the third portion (e.g. data segment  2 ) to create second manipulated data and sends the second manipulated data to DSN memory  2  for storage therein. Next, DS processing unit  2  sends the fourth portion to DS processing unit  3 . DS processing units  3 -(N- 1 ) may operate in accordance with the method described for DS processing unit  2 . In the example of operation continued, DS processing unit N receives data segment N from DS processing unit N- 1 . Next, DS processing unit N manipulates data segment N to create Nth manipulated data and sends the Nth manipulated data to DSN memory N for storage therein. 
     Each DS processing unit of the plurality of DS processing units manipulates a corresponding data segment to create corresponding manipulated data in accordance with a data manipulation approach. Next, the DS processing unit sends the manipulated data to one or more DS units of a corresponding DSN memory in accordance with the data manipulation approach. For example, DS processing unit  1  sends a decode threshold number of sections (e.g., sections  1 -k) of data segment  1  to a corresponding decode threshold number of DS units (e.g., DS units  1 -k) of DSN memory  1 . The DS processing unit and/or a DS unit may update a directory and/or a storage location table subsequent to storing the data in the plurality of DSN memories. The method of operation of each of the plurality of DS processing units when the data manipulation approach indicates to send the decode threshold number of sections (e.g., sections  1 -k) of data segment  1  to the corresponding decode threshold number of DS units of the DSN memory is described in greater detail with reference to  FIG. 16B . A decode threshold number of DS units communicates slice components with each other DS unit of the plurality of DS units associated with a DSN memory to facilitate storing of a pillar width number of encoded data slices in DS units  1 -n of each DSN memory of the plurality of DSN memories. The method of operation of each of the DS units of the plurality of DS units when the data manipulation approach indicates to send the decode threshold number of sections (e.g., sections  1 -k) of data segment  1  to the corresponding decode threshold number of DS units of the DSN memory is described in greater detail with reference to  FIG. 16C-E . 
     In a data retrieval example of operation, each DS processing unit retrieves manipulated data from a corresponding DSN memory in accordance with the data manipulation approach, decodes the manipulated data to produce a corresponding data segment in accordance with the data manipulation approach, sends the data segment to at least one other DS processing unit in accordance with a data segmentation approach, and aggregates data segments to produce the data in accordance with the data segmentation approach. 
       FIG. 16B  is a flowchart illustrating another example of storing data, which include similar steps to  FIG. 15B . The method begins with steps  300 - 304  of  FIG. 15  B where a processing module (e.g., of a dispersed storage (DS) processing unit) receives (e.g., from a user device, from a DS processing unit, from a DS unit) a data storage request message that includes upstream data, determines a storage portion (e.g., a data segment) of the upstream data, and determines whether to form downstream data based on the storage portion. The method branches to step  328  when the processing module determines to not form downstream data. The method continues to step  306  of  FIG. 15B  when the processing module determines to form downstream data. The method continues with steps  306 - 310  of  FIG. 15B  where the processing module determines downstream data based on the storage portion and the upstream data, determines a recipient to receive the downstream data, and sends the downstream data to the recipient when the processing module determines to form downstream data. 
     The method continues at step  328  where the processing module partitions the storage portion to produce a decode threshold number of segment sections in accordance with error coded dispersal storage function parameters and based on a data manipulation approach. For example, the processing module partitions the storage portion to produce the decode threshold number of segment sections wherein each of the segment sections is substantially the same size. For instance, the processing module partitions a 3 megabyte (MB) storage portion to produce three segment sections wherein each of the segment sections is 1 MB when the error coded dispersal storage function parameters indicate a decode threshold of 3 and the data manipulation approach includes guidance to create and store the decode number of segment sections. The method continues at step  312  of  FIG. 15B  where the processing module determines a DS unit storage set. 
     The method continues at step  330  where the processing module determines a decode threshold number of DS units of the DS unit storage set to produce selected DS units. The determination may be based on one or more of the data manipulation approach, a DS unit capability indicator, a DS unit availability indicator, a list, a message, and a query. The method continues at step  332  where the processing module sends write request messages to the selected DS units that includes the decode threshold number of segment sections. For example, the processing module sends a write request message to DS unit  1  that includes segment section  1 . As another example, the processing module sends a write request message to DS unit  2  that includes segment section  2 . In addition, the processing module may update directory information and/or a storage location table. 
       FIG. 16C  is an algorithm illustrating an example of encoding data including a 5 by 3 generator matrix  334 , a 3 by 1 data matrix  336 , and a resulting 5 by 1 matrix  338  of encoded data slices  1 - 5 . Such encoding may be utilized to dispersed storage error encode data (e.g., a segment section, a data segment) to produce a set of encoded data slices. The encoding of each slice of the set includes a plurality of intermediate steps. For example, the 5 by 3 generator matrix  334  is multiplied times the 3 by 1 data matrix  336  to produce the 5 by 1 matrix of encoded data slices  1 - 5 . The example corresponds to error coded dispersal storage function parameters including a pillar width of 5 and a decode threshold of 3. Each slice may be calculated by adding three products of an entry of the generator matrix times an entry of the data matrix. For instance, slice  1  is encoded as ax+by+cz. Note that a system security improvement may be realized by subdividing the execution of the encoding of slices between a plurality of processing modules. For example, note that the encoding of a slice  1  may be accomplished by adding three slice components associated with slice  1  wherein three processing modules multiply a different column of the generator matrix times a different portion of the data. As such, a security improvement may be provided by utilizing a plurality of processing modules to generate slices wherein each processing module only utilizes one column of the generator matrix and one portion of the data. 
       FIG. 16D  is a processing module task map illustrating an example of determining processing module assignments. For example, a processing module assignment to calculate a slice  1  is divided amongst three processing modules. For instance, a processing module  1  associated with a DS unit  1  encodes the “ax” product as a slice component, a processing module  2  associated with a DS unit  2  encodes the “by” product as another slice component, and a processing module  3  associated with a DS unit  3  encodes the “cz” product as another slice component. The processing module  1  may subsequently aggregate the three products (e.g., the three slice components) to produce slice  1 . Processing modules  1 - 3  are also assigned to subsequently encode the “dx”, “ey”, “fz”, “gx”, “hy”, “iz”, “jx”, “ky”, “lz”, “mx”, “ny”, and “oz” products wherein each processing module utilizes just one column of the generator matrix. A security improvement may be provided by limiting a particular processing module to one column of the encoding matrix. 
       FIG. 16E  is a flowchart illustrating another example of storing an encoded data slice, which include similar steps to  FIG. 15B . The method begins with step  340  where a processing module (e.g., of a dispersed storage (DS) unit associated with a decode threshold number of DS units) receives a write request message that includes a segment section. The write storage request message may include one or more of a data identifier (ID), the segment section, a user device ID, a vault ID, a DS processing unit ID, error coding dispersal storage function parameters, pillar selection information, a data manipulation approach, a source name, a stored portion indicator, a data size indicator, a data type indicator, a priority indicator, a security indicator, and a performance indicator. 
     The method continues at step  342  where the processing module partially dispersed storage error encodes the segment section to produce a set of slice components. For example, the processing module multiplies the segment section times a column of an encoding matrix to produce a pillar width number of slice components. As another instance, as illustrated in  FIG. 16D , a processing module  1  associated with a DS unit  1  produces column  1  slice components of ax for slice  1 , dx for slice  2 , gx for slice  3 , jx for slice  4 , and mx for slice  5  when the pillar width is  5  and the decode threshold is  3 . As yet another instance, a processing module  2  associated with a DS unit  2  produces column  2  slice components of by for slice  1 , ey for slice  2 , by for slice  3 , ky for slice  4 , and ny for slice  5  when the pillar width is 5 and the decode threshold is  3 . As a still further instance, a processing module  3  associated with a DS unit  3  produces column  3  slice components of cz for slice  1 , fz for slice  2 , iz for slice  3 , lz for slice  4 , and oz for slice  5  when the pillar width is 5 and the decode threshold is 3. 
     The method continues at step  312   FIG. 15B  where the processing module determines a DS unit storage set. The method continues at step  344  where the processing module sends a set of write request messages to each DS unit (e.g., a pillar width number of DS units) of the DS unit storage set that includes the slice components (e.g., a pillar width number of slice components). For example, the processing module  1  sends the set of write request message to DS units  2 - 5  associated with column  1  of an encoding matrix, wherein the write request message to DS unit  2  includes a slice component corresponding to slice  2 , the write request message to DS unit  3  includes a slice component corresponding to slice  3 , the write request message to DS unit  4  includes a slice component corresponding to slice  4 , and the write request message to DS unit  5  includes a slice component corresponding to slice  5 . As another example, the processing module  2  sends the set of write request message to DS units  1 ,  3 - 5  associated with column  2  of an encoding matrix, wherein the write request message to DS unit  1  includes a slice component corresponding to slice  1 , the write request message to DS unit  3  includes a slice component corresponding to slice  3 , the write request message to DS unit  4  includes a slice component corresponding to slice  4 , and the write request message to DS unit  5  includes a slice component corresponding to slice  5 . As yet another example, the processing module  3  sends the set of write request message to DS units  1 - 2 ,  4 - 5  associated with column  3  of an encoding matrix, wherein the write request message to DS unit  1  includes a slice component corresponding to slice  1 , the write request message to DS unit  2  includes a slice component corresponding to slice  2 , the write request message to DS unit  4  includes a slice component corresponding to slice  4 , and the write request message to DS unit  5  includes a slice component corresponding to slice  5 . 
     The method continues at step  346  where the processing module (e.g., associated with each of the DS units of the DS unit storage set) receives write request messages that includes a decode threshold number of slice components corresponding to a common slice. Each DS unit of the decode threshold number of DS units provide at least one of the decode threshold number of slice components to the same DS unit. For example, DS unit  1  receives write request messages from DS unit  2  and DS unit  3  and utilizes an additional slice component with reference to slice  1  created by DS unit  1 . The method continues at step  348  where the processing module sums the slice components to produce an encoded data slice. The method continues at step  350  where the processing module stores encoded data slice. Next, the processing module updates directory information and/or a storage location table. 
       FIG. 17A  is a schematic block diagram of another embodiment of a computing system. The system includes a user device  12 , a plurality of dispersed storage (DS) processing units  1 -N, a plurality of dispersed storage network (DSN) memories  1 -N that each include a plurality of DS units  1 -n. Alternatively, a plurality of DS processing modules and/or DS modules may be utilized to implement the plurality of DS processing units  1 -N. Alternatively, the plurality of DSN memories  1 -N may be implemented with one DSN memory. Each DSN memory of the plurality of DSN memories  1 -N may include a different number of DS units when more than one DSN memory is utilized. 
     In an example of operation, the user device  12  sends data  280  to DS processing unit  1  for storage in the plurality of DSN memories. DS processing unit  1  receives the data  280  and partitions the data  280  into a first portion and a second portion in accordance with a segmentation approach. Next, DS processing unit  1  manipulates the first portion (e.g. data segment  1 ) to create first manipulated data and sends the first manipulated data to DSN memory  1  for storage therein. Next, DS processing unit  1  sends the second portion to DS processing unit  2 . DS processing unit  2  receives the second portion and partitions the second portion into a third portion and a fourth portion in accordance with the segmentation approach. Next, DS processing unit  2  manipulates the third portion (e.g. data segment  2 ) to create second manipulated data and sends the second manipulated data to DSN memory  2  for storage therein. Next, DS processing unit  2  sends the fourth portion to DS processing unit  3 . DS processing units  3 -(N- 1 ) may operate in accordance with the method described for DS processing unit  2 . In the example of operation continued, DS processing unit N receives data segment N from DS processing unit N- 1 . Next, DS processing unit N manipulates data segment N to create Nth manipulated data and sends the Nth manipulated data to DSN memory N for storage therein. 
     Each DS processing unit of the plurality of DS processing units manipulates a corresponding data segment to create corresponding manipulated data in accordance with a data manipulation approach. Next, the DS processing unit sends the manipulated data to one or more DS units of a corresponding DSN memory in accordance with the data manipulation approach. For example, DS processing unit  1  sends data segment  1  to a decode threshold number of DS units (e.g., DS units  1 -k) of DSN memory  1 . The DS processing unit and/or a DS unit may update a directory and/or a storage location table subsequent to storing the data in the plurality of DSN memories. The method of operation of each of the plurality of DS processing units when the data manipulation approach indicates to send the data segment to the decode threshold number of DS units of the DSN memory is described in greater detail with reference to  FIG. 17B . Note that decode threshold number of DS units produce and send slice partials to other DS unit (e.g., not of the decode threshold number of DS units) of the plurality of DS units associated with a DSN memory to facilitate storing of a pillar width number of encoded data slices in DS units  1 -n of each DSN memory of the plurality of DSN memories. The method of operation of each of the DS units of the plurality of DS units when the data manipulation approach indicates to send the data segment to the decode threshold number of DS units of the DSN memory is described in greater detail with reference to  FIGS. 17C-F . 
     In a data retrieval example of operation, each DS processing unit retrieves manipulated data from a corresponding DSN memory in accordance with the data manipulation approach, decodes the manipulated data to produce a corresponding data segment in accordance with the data manipulation approach, sends the data segment to at least one other DS processing unit in accordance with a data segmentation approach, and aggregates data segments to produce the data in accordance with the data segmentation approach. 
       FIG. 17B  is a flowchart illustrating another example of storing data, which include similar steps to  FIG. 15B . The method begins with steps  300 - 304  of  FIG. 15  B where a processing module (e.g., of a dispersed storage (DS) processing unit) receives (e.g., from a user device, from a DS processing unit, from a DS unit) a data storage request message that includes upstream data, determines a storage portion (e.g., a data segment) of the upstream data, and determines whether to form downstream data based on the storage portion. The method branches to step  312  of  FIG. 15B  when the processing module determines to not form downstream data. The method continues to step  306  of  FIG. 15B  when the processing module determines to form downstream data. The method continues with steps  306 - 310  of  FIG. 15B  where the processing module determines downstream data based on the storage portion and the upstream data, determines a recipient to receive the downstream data, and sends the downstream data to the recipient when the processing module determines to form downstream data. 
     The method continues with step  312  of  FIG. 15B  where the processing module determines a DS unit storage set. The method continues with step  330  of  FIG. 16B  where the processing module determines a decode threshold number of DS units of the DS unit storage set to produce selected DS units. The method continues at step  352  where the processing module sends write request messages to the selected DS units that includes the storage portion (e.g., a data segment corresponding to the processing module). For example, a processing module  1  of a dispersed storage processing unit  1  sends a write request message to DS units  1 - 3  that includes a data segment  1  as the storage portion when the decode threshold is  3 . In addition, the processing module may update directory information and/or a storage location table. 
       FIG. 17C  is an algorithm illustrating another example of encoding data including a 5 by 3 generator matrix  334 , a 3 by 1 data matrix  336 , and a resulting 5 by 1 matrix  338  of encoded data slices  1 - 5 . Such encoding may be utilized to dispersed storage error encode data (e.g., a segment section, a data segment) to produce a set of encoded data slices. The encoding of each slice of the set includes a plurality of intermediate steps. For example, the 5 by 3 generator matrix  334  is multiplied times the 3 by 1 data matrix  336  to produce the 5 by 1 matrix of encoded data slices  1 - 5 . The example corresponds to error coded dispersal storage function parameters including a pillar width of 5 and a decode threshold of 3. Each slice may be calculated by adding three products of an entry of the generator matrix times an entry of the data matrix. For instance, slice  1  is encoded as ax+by+cz. A system security improvement may be realized by subdividing the execution of the encoding of slices between a plurality of processing modules. For example, the encoding of a slice  1  requires multiplying row one of a generator matrix times the data. As such, a security improvement may be provided by utilizing a plurality of processing modules to generate slices wherein each processing module only utilizes one row of the generator matrix and the data. 
       FIG. 17D  is a dispersed storage (DS) unit task map illustrating another example of determining DS unit assignments. For example, a processing module assignment to calculate a slice  1  is assigned to processing module  1 . For instance, processing module  1  associated with a DS unit  1  encodes data by multiplying a first row of an encoding matrix times the data to produce an “ax” product, a “by” product, and a “cz” product. The processing module  1  may subsequently aggregate the three products (e.g., the three slice components) to produce slice  1 . Processing module  2  associated with a DS unit  2  is assigned to create a slice  2 , and a processing module  3  associated with a DS unit  3  is assigned to create a slice  3 . Processing module  1  is assigned to create a slice partial  4 _ 1  (e.g., to reproduce slice  4  utilizing information from slice  1 ), processing module  1  is assigned to create a slice partial  5 _ 1  (e.g., to reproduce slice  5  utilizing information from slice  1 ), processing module  2  is assigned to create a slice partial  4 _ 2  (e.g., to reproduce slice  4  utilizing information from slice  2 ), processing module  2  is assigned to create a slice partial  5 _ 2  (e.g., to reproduce slice  5  utilizing information from slice  2 ), and processing module  3  is assigned to create a slice partial  4 _ 3  (e.g., to reproduce slice  4  utilizing information from slice  3 ), processing module  3  is assigned to create a slice partial  5 _ 3  (e.g., to reproduce slice  5  utilizing information from slice  3 ). In an example of operation, processing modules  1 - 3  send their two slice partials to processing modules  4 - 5  associated with DS units  4 - 5 . Next, processing module  4  decodes three received slice partials to produce slice  4  and processing module  5  decodes three received slice partials to produce slice  5 . 
       FIG. 17E  is a flowchart illustrating another example of storing an encoded data slice, which include similar steps to  FIG. 16E . The method begins with step  340  of  FIG. 16E  where a processing module (e.g., of a dispersed storage (DS) unit) receives a write request message that includes a segment. The method continues at step  354  where the processing module partially dispersed storage error encodes the segment to produce an encoded data slice. For example, the processing module multiplies a row of an encoding matrix times the segment to produce the encoded data slice. The method continues at step  356  where the processing module determines remaining DS units. The remaining DS units may be outside of a decode threshold number of DS units of a DS unit storage set. The determination may be based on one or more of a message, a query, and a predetermination. The method continues at step  358  where the processing module generates a slice partial for each of the remaining DS units. The method continues at step  360  where the processing module sends the slice partials to the remaining DS units. 
       FIG. 17F  is a flowchart illustrating another example of storing an encoded data slice. The method begins with step  362  where a processing module receives a decode threshold number of slice partials (e.g., from a decode threshold number of dispersed storage (DS) units). The method continues at step  364  where the processing module decodes the decode threshold number of slice partials to produce an encoded data slice. For example, the processing module utilizes the logical XOR function to produce the encoded data slice =slice partial  1  XOR slice partial  2  XOR slice partial  3  etc. The method continues at step  366  where the processing module stores encoded data slice and updates directory information and/or a storage location table. 
       FIG. 18A  is a schematic block diagram of an embodiment of a dispersed storage (DS) unit  16  that includes a control module  370 , a solid state memory  372 , and a plurality of magnetic memories  1 -M. The control module  370  may be implemented utilizing a computing core  26 . The solid-state memory may be implemented utilizing one or more memory devices utilizing one or more memory technologies including NAND Flash technology, static random access memory (RAM), dynamic random access memory (DRAM), or any other memory technology that provides low access latency with respect to magnetic memory technology. The plurality of magnetic memories  1 -N may be implemented utilizing a hard disk drive magnetic media to provide high capacity memory for slice storage and retrieval at a lower cost than the solid-state memory. Alternatively, optically based storage may be utilized as the magnetic memories  1 -M. 
     The control module  370  is operably coupled to the solid-state memory  372  to facilitate reading and writing of storage information  376 . The storage information  376  may include one or more of a slice name, slice integrity information, a magnetic memory identifier (ID), an offset, an encoded data slice, and metadata. The control module  370  is operably coupled to the plurality of magnetic memories  1 -M to facilitate reading and writing of encoded data slices. 
     In an example of operation, the control module  270  receives control information  374  that includes one or more of a request opcode, a slice name, integrity information, and an encoded data slice  11 . The control module  370  obtains integrity information associated with the encoded data slice (e.g., calculating a cyclic redundancy check over the encoded data slice; receiving the integrity information as part of the control information  374 ). The control module  270  determines a magnetic memory ID associated with at least one of the magnetic memories of the plurality of the magnetic memories  1 -M to store the encoded data slice. Next, the control module  370  stores the slice name, the integrity information and the magnetic memory ID as storage information  376  in the solid-state memory. The control module  370  stores the encoded data slice  11  in the magnetic memory corresponding to the magnetic memory ID. 
     As another example of operation, the control module  270  receives control information  374  indicating a read request from a requester that includes a slice name corresponding to an encoded data slice to be read. The control module  370  accesses the solid-state memory utilizing the slice name to retrieve integrity information associated with the encoded data slice and a magnetic memory ID associated with storage of the encoded data slice. The control module  370  retrieves the encoded data slice from the magnetic memory corresponding to the magnetic memory ID to produce a retrieved encoded data slice. The control module  370  generates integrity information of the retrieved encoded data slice (e.g., calculating a cyclic redundancy check over the retrieved encoded data slice). The control module  270  determines whether the generated integrity information compares favorably to the retrieved integrity information (e.g., favorable when substantially the same). The control module  370  sends the retrieved encoded data slice  11  to the requester as the encoded data slice  11  when the comparison is favorable. The method of operation is discussed in greater detail with reference to  FIGS. 18B-19D . 
       FIG. 18B  is a flowchart illustrating another example of storing an encoded data slice. The method begins with step  378  where a processing module (e.g., of a dispersed storage (DS) unit) receives a write request message that includes an encoded data slice for storage. The write request message may include one or more of the encoded data slice, a slice name, a source name, a user device identifier (ID), a data ID, a performance indicator, and slice integrity information. The method continues at step three where the processing module obtains integrity information associated with the encoded data slice. Such obtaining may include one or more of receiving the slice integrity information as the integrity information and calculating the integrity information (e.g., utilizing a hash in function to compute a hash over the encoded data slice). 
     The method continues at step  382  where the processing module determines a magnetic memory for storing the encoded data slice to produce a magnetic memory ID. The determination may be based on one or more of a magnetic memory available capacity indicator, a magnetic memory performance indicator, a slice size indicator, and the performance indicator. For example, the processing module determines to utilize magnetic memory  3  when a magnetic memory performance indicator associated with memory  3  compares favorably with the performance indicator. As another example, the processing module determines to utilize magnetic memory  5  when a magnetic memory available capacity indicator associated with memory  5  compares favorably to the slice size indicator. 
     The method continues at step  384  where the processing module determines an offset within the magnetic memory for storing the encoded data slice. The determination may be based on one or more of a magnetic memory available capacity indicator associated with the magnetic memory, a magnetic memory performance indicator associated with the magnetic memory, the slice size indicator, and a current offset associated with the magnetic memory. For example, the processing module determines to store the entire encoded data slice at an offset of 100 within magnetic memory  6  when the magnetic memory available capacity indicator associated with the magnetic memory  6  compares favorably to the slice size indicator. As another example, the processing module determines to store a first portion of the encoded data slice at an offset of 300 within magnetic memory  6  and a remaining portion of the encoded data slice at an offset of 4300 when the magnetic memory available capacity indicator associated with the magnetic memory  6  compares favorably to the slice size indicator for two data blocks at offsets  300  and  4300 . 
     The method continues at step  36  where the processing module aggregates storage information associated with the encoded data slice that includes the integrity information. The method continues at step  388  where the processing module stores the encoded data slice at the offset in the magnetic memory corresponding to the magnetic memory ID. The method continues at step  390  where the processing module stores the storage information in a solid-state memory. 
       FIG. 18C  is a flowchart illustrating an example of retrieving an encoded data slice. The method begins with step  392  where a processing module (e.g., of a dispersed storage (DS) unit) receives a retrieval request message from a requester to retrieve an encoded data slice associated with a slice name of the request. The retrieval request message may include one or more of the slice name, a source name, a user device identifier (ID), a data ID, a performance indicator, and slice integrity information. The method continues at step  394  where the processing module retrieves storage information from a solid-state memory based on the slice name. For example, the processing module utilizes the slice name as an index into a table structure of storage information to retrieve the storage information. 
     The method continues at step  396  where the processing module extracts an offset and a magnetic memory ID from the storage information. Next, the processing module retrieves an encoded data slice at the offset in a magnetic memory corresponding to the magnetic memory ID to produce a retrieved encoded data slice. The method continues at step  398  where the processing module determines calculated integrity information corresponding to the retrieved encoded data slice. For example, the processing module calculates a hash over the retrieved encoded data slice to produce the calculated integrity information. 
     The method continues at step  400  where the processing module extracts integrity information from the storage information. Next, the processing module determines whether the calculated integrity information compares favorably to the integrity information. For example, the processing module determines that the calculated integrity information compares favorably to the integrity information when the calculated integrity information is substantially the same as the integrity information. The method branches to step  404  when the processing module determines that the calculated integrity information compares favorably to the integrity information. The method continues to step  402  when the processing module determines that the calculated integrity information compares unfavorably to the integrity information. 
     The method continues at step  402  where the processing module facilitates slice rebuilding when the calculated integrity information compares unfavorably to the integrity information. For example, the processing module sends a rebuilding message to a storage integrity processing unit that includes the slice name. As another example, the processing module sends (e.g., to the requester and/or to a dispersed storage managing unit) an error message that includes the slice name. The method continues at step  404  where the processing module sends the retrieved encoded data slice as the encoded data slice to the requester when the calculated integrity information compares favorably to the integrity information. 
       FIG. 19A  is a flowchart illustrating another example of storing an encoded data slice. The method begins with step  410  where a processing module (e.g., of a dispersed storage (DS) module, of a DS unit) receives (e.g., from a user device, from a DS processing module, from a DS processing unit, from a DS unit) an encoded data slice for storage. The method continues at step  412  where the processing module obtains metadata associated with the encoded data slice. The metadata includes one or more of a slice name, an encoded data slice size indicator, integrity information, a data type, an estimated access frequency, a priority requirement, a performance requirement, and a user identifier (ID). The obtaining includes at least one of receiving the metadata (e.g., with the encoded data slice), generating at least a portion of the metadata based on the encoded data slice, retrieving the metadata, outputting a query to request the metadata, and receiving a message that includes the metadata. 
     The method continues at step  414  where the processing module interprets the metadata to determine whether the encoded data slice is to be stored in a first access speed memory or a second access speed memory, wherein the first access speed memory has a higher data access rate than the second access speed memory. For example, the first access speed memory includes a plurality of solid-state memory devices and the second access speed memory includes one or more hard drive memory devices. 
     The interpreting the metadata includes at least one of interpreting the metadata to determine an estimated access frequency of the encoded data slice, wherein, when the estimated access frequency compares favorably to an access frequency threshold (e.g., favorable when the estimated access frequency is greater than the access frequency threshold), indicating that the encoded data slice is to be stored in the first access speed memory, interpreting the metadata to determine a data type of the encoded data slice, wherein, when the data type is a first data type, indicating that the encoded data slice is to be stored in the first access speed memory, interpreting the metadata to determine a user identifier of the encoded data slice, wherein, when the user identifier is a first user type, indicating that the encoded data slice is to be stored in the first access speed memory, interpreting the metadata to determine a priority requirement of the encoded data slice, wherein, when the priority requirement is a first priority type, indicating that the encoded data slice is to be stored in the first access speed memory, and interpreting the metadata to determine a performance requirement of the encoded data slice, wherein, when the performance requirement is a first performance type (e.g., above average performance), indicating that the encoded data slice is to be stored in the first access speed memory. 
     Alternatively, or in addition to, the processing module interprets the metadata to determine whether the encoded data slice is to be stored in the first access speed memory, the second access speed memory, or a third access speed memory, wherein the second access speed memory has a higher data access rate than the third access speed memory and stores the encoded data slice in a memory device of the third access speed memory when the encoded data slice is to be stored in the third access speed memory. 
     The method branches to step  418  when the processing module determines that the encoded data slice is to be stored in the second access speed memory. The method continues to step  416  when the processing module determines that the encoded data slice is to be stored in the first access speed memory. The method continues at step  416  where the processing module facilitates storing the encoded data slice in a memory device of the first access speed memory when the encoded data slice is to be stored in the first access speed memory. The facilitating includes at least one of storing the encoded data slice in the memory device of the first access speed memory, sending the encoded data slice to the memory device of the first access speed memory, and outputting the encoded data slice to intermediary processing module for storage in the memory device of the first access speed memory. Such facilitating may apply to one or more of storing, sending, receiving, transferring, and retrieving. 
     The method continues at step  418  where the processing module facilitates storing the encoded data slice in a memory device of the second access speed memory when the encoded data slice is to be stored in the second access speed memory. The method continues at step  420  where the processing module generates storage information to include one or more of a slice name associated with the encoded data slice, a memory device identifier (ID) of the memory device of the first or the second access speed memory, a memory device storage location associated with the storing of the encoded data slice (e.g., an offset), and at least some of the metadata. The method continues at step  422  where the processing module stores the storage information in an information memory device of the first access speed memory. For sample, the processing module stores the storage information in the memory device of the first access speed memory. 
     The method continues at step  424  where the processing module retrieves the storage information from the information memory device. The retrieving may include at least one of determining to retrieve the storage information (e.g., based on one or more of a timer expiration, access of the encoded data slice, a request), outputting a request for the storage information to the information memory device, and receiving the storage information from the information memory device. The method continues at step  426  where the processing module updates the storage information based on one or more of historical access information, a reprioritization message, and updated metadata to produce updated storage information. For example, the processing module updates the storage information to include historical access information that includes an actual data access frequency. As another example, the processing module updates to storage information to include an elevation of a priority level based on receiving the reprioritization message. The method continues at step  428  or the processing module stores the updated storage information in the information memory device. The updated storage information maybe subsequently utilized to determine whether to transfer the encoded data slice between the memory device of the first access speed memory and the memory device of the second access speed memory. A method to determine whether to transfer the encoded data slice is discussed in greater detail with reference to  FIG. 19B . 
       FIG. 19B  is a flowchart illustrating an example of transferring an encoded data slice. The method begins with step  430  where a processing module (e.g., of a dispersed storage (DS) module, of a DS unit) obtains data access frequency information regarding a stored encoded data slice. The data access frequency information includes one or more of read requests regarding the stored encoded data slice within a given time period, write requests regarding the stored encoded data slice within a time frame, duration of storage of the stored encoded data slice, data size of the stored encoded data slice, and memory availability. 
     The method continues at step  432  where the processing module transfers the stored encoded data slice from a first access speed memory to a second access speed memory when the stored encoded data slice is stored in the first access speed memory and the data access frequency information compares unfavorably to a first access frequency threshold wherein the first access speed memory has a higher data access rate than the second access speed memory. The data access frequency information comparing unfavorably to the first access frequency threshold includes one or more of quantity of read requests regarding the stored encoded data slice within a given time period compares unfavorably to a read request threshold (e.g., unfavorable when read requests regarding the stored encoded data slice within the given time period is less than the first read request threshold of the first access frequency threshold), quantity of write requests regarding the stored encoded data slice within a time frame compares unfavorably to a read request threshold, duration of storage of the stored encoded data slice in the first access speed memory compares unfavorably to a storage duration threshold, and data size of the stored encoded data slice and memory availability of the first access speed memory compares unfavorably to a storage availability threshold. 
     The method continues at step  432  where the processing module transfers the stored encoded data slice from the second access speed memory to the first access speed memory when the stored encoded data slice is stored in the second access speed memory and the data access frequency information compares favorably to a second access frequency threshold. The data access frequency information comparing favorably to the second access frequency threshold includes one or more of quantity of read requests regarding the stored encoded data slice within a given time period compares favorably to a read request threshold (e.g., favorable when read requests regarding the stored encoded data slice within the given time period is greater than the read request threshold of the second access frequency threshold), and quantity of write requests regarding the stored encoded data slice within a time frame compares favorably to a read request threshold. 
       FIG. 19C  is a block diagram of another storing module  231  that operates in accordance with the method described in  FIG. 19A . The storing module  231  is a module that includes one or more sub-modules, which include a receive module  233 , a determine memory module  235 , a data storing module  237 , a generate storage information module  239 , an update storage information module  241 , and a store storage information module  243 . 
     The receive module  233  facilitates receiving (e.g., from a dispersed storage (DS) processing unit  16 ) an encoded data slice  253  for storage. The determine memory module  235  obtains metadata associated with the encoded data slice  253 . The determine memory module  235  interprets the metadata to determine whether the encoded data slice  253  is to be stored in a first access speed memory  245  (e.g., the first access speed memory may include a plurality of solid-state memory devices) or a second access speed memory  247  (e.g., the second access speed memory includes one or more hard drive memory devices), wherein the first access speed memory has a higher data access rate than the second access speed memory. Alternatively, the determine memory module  235  module interprets the metadata to determine whether the encoded data slice is to be stored in the first access speed memory  245 , the second access speed memory  247 , a third access speed memory  249 , or up through an Nth access speed memory  251 , wherein the second access speed memory  247  has a higher data access rate than the third access speed memory  249 . 
     The determine memory module  235  interprets the metadata by one or more of interpreting the metadata to determine an estimated access frequency of the encoded data slice  253 , wherein, when the estimated access frequency compares favorably to an access frequency threshold, indicating that the encoded data slice is to be stored in the first access speed memory  245 ; interpreting the metadata to determine a data type of the encoded data slice  253 , wherein, when the data type is a first data type, indicating that the encoded data slice is to be stored in the first access speed memory  245 ; interpreting the metadata to determine a user identifier of the encoded data slice, wherein, when the user identifier is a first user type, indicating that the encoded data slice  253  is to be stored in the first access speed memory  245 ; interpreting the metadata to determine a priority requirement of the encoded data slice, wherein, when the priority requirement is a first priority type, indicating that the encoded data slice  253  is to be stored in the first access speed memory  245 ; and interpreting the metadata to determine a performance requirement of the encoded data slice, wherein, when the performance requirement is a first performance type, indicating that the encoded data slice  253  is to be stored in the first access speed memory  245 . 
     The data storing module  237  facilitates storing the encoded data slice  253  in a memory device of the first access speed memory  245  when the encoded data slice  253  is to be stored in the first access speed memory  245  and facilitates storing the encoded data slice in a memory device of the second access speed memory  247  when the encoded data slice  253  is to be stored in the second access speed memory  247 . Alternatively, the data storing module  237  facilitates storing the encoded data slice  253  in a memory device of the third access speed memory  249  when the encoded data slice  253  is to be stored in the third access speed memory  249 . 
     The generate storage information module  239  generates storage information  255  to include one or more of a slice name associated with the encoded data slice  253 , a memory device identifier (ID) of the memory device of the first or the second access speed memory, a memory device storage location associated with the storing of the encoded data slice, and at least some of the metadata. The update storage information module  241  retrieves the storage information  257  (e.g. previously stored), from an information memory device  263  and updates the storage information  257  based on one or more of historical access information, a reprioritization message, and updated metadata to produce updated storage information  259 . The information memory device  263  may be implemented as a separate memory device and/or as any one of the first access speed memory  245  through the Nth access speed memory  251 . The store storage information module  243  facilitates storing the storage information to  255  in the information memory device  263 . For example, the store storage information module  243  stores for storage information  255  in the first access speed memory  245  when the first access speed memory  245  serves as the information memory device  263 . Alternatively, the store storage information module  243  stores the updated storage information  259  in the information memory device  263  as updated storage information  261 . 
       FIG. 19D  is a block diagram of another storing module  271  that operates in accordance with the method described in  FIG. 19B . The storing module  271  is a module that includes one or more sub-modules, which include an obtain data access frequency information module  273  and a slice transfer module  275 . 
     The obtain data access frequency information module  273  contains data access frequency information regarding a stored encoded data slice  253 . The data access frequency information includes one or more of read requests regarding the stored encoded data slice within a given time period, write requests regarding the stored encoded data slice within a time frame, duration of storage of the stored encoded data slice, data size of the stored encoded data slice, and memory availability. 
     The slice transfer module  275  facilitates transferring the stored encoded data slice  253  from a memory of a first access speed memory to  245 , a second access speed memory  247 , a third access speed memory  249 , through an Nth access speed memory  251  to a different memory of the memories  245 - 251 . For example, the slice transfer module  275  facilitates transferring of the encoded data slice  253  from the first access speed memory  245  to the second access speed memory  247  when the stored encoded data slice  253  is stored in the first access speed memory  245  and the data access frequency information  277  compares unfavorably to a first access frequency threshold, wherein the first access speed memory  245  has a higher data access rate than the second access speed memory  247 . As another example, the slice transfer module  275  facilitates transferring of the encoded data slice  253  the stored encoded data slice  253  from the second access speed memory  247  to the first access speed memory to  45  when the stored encoded data slice  253  is stored in the second access speed memory  247  and the data access frequency information  277  compares favorably to a second access frequency threshold. 
     The data access frequency information  277  comparing unfavorably to the first access frequency threshold includes one or more of quantity of read requests regarding the stored encoded data slice  253  within a given time period compares unfavorably to a read request threshold, quantity of write requests regarding the stored encoded data slice  253  within a time frame compares unfavorably to a read request threshold, duration of storage of the stored encoded data slice  253  in the first access speed memory  245  compares unfavorably to a storage duration threshold, and data size of the stored encoded data slice  253  and memory availability of the first access speed memory  245  compares unfavorably to a storage availability threshold. The data access frequency information  277  comparing favorably to the second access frequency threshold includes one or more of quantity of read requests regarding the stored encoded data slice within a given time period compares favorably to a read request threshold and quantity of write requests regarding the stored encoded data slice within a time frame compares favorably to a read request threshold. 
     It is noted that terminologies as may be used herein such as bit stream, stream, signal sequence, etc. (or their equivalents) have been used interchangeably to describe digital information whose content corresponds to any of a number of desired types (e.g., data, video, speech, text, graphics, audio, etc. any of which may generally be referred to as ‘data’). 
     As may be used herein, the terms “substantially” and “approximately” provides an industry-accepted tolerance for its corresponding term and/or relativity between items. For some industries, an industry-accepted tolerance is less than one percent and, for other industries, the industry-accepted tolerance is  10  percent or more. Other examples of industry-accepted tolerance range from less than one percent to fifty percent. Industry-accepted tolerances correspond to, but are not limited to, component values, integrated circuit process variations, temperature variations, rise and fall times, thermal noise, dimensions, signaling errors, dropped packets, temperatures, pressures, material compositions, and/or performance metrics. Within an industry, tolerance variances of accepted tolerances may be more or less than a percentage level (e.g., dimension tolerance of less than +/−1%). Some relativity between items may range from a difference of less than a percentage level to a few percent. Other relativity between items may range from a difference of a few percent to magnitude of differences. 
     As may also be used herein, the term(s) “configured to”, “operably coupled to”, “coupled to”, and/or “coupling” includes direct coupling between items and/or indirect coupling between items via an intervening item (e.g., an item includes, but is not limited to, a component, an element, a circuit, and/or a module) where, for an example of indirect coupling, the intervening item does not modify the information of a signal but may adjust its current level, voltage level, and/or power level. As may further be used herein, inferred coupling (i.e., where one element is coupled to another element by inference) includes direct and indirect coupling between two items in the same manner as “coupled to”. 
     As may even further be used herein, the term “configured to”, “operable to”, “coupled to”, or “operably coupled to” indicates that an item includes one or more of power connections, input(s), output(s), etc., to perform, when activated, one or more its corresponding functions and may further include inferred coupling to one or more other items. As may still further be used herein, the term “associated with”, includes direct and/or indirect coupling of separate items and/or one item being embedded within another item. 
     As may be used herein, the term “compares favorably”, indicates that a comparison between two or more items, signals, etc., indicates an advantageous relationship that would be evident to one skilled in the art in light of the present disclosure, and based, for example, on the nature of the signals/items that are being compared. As may be used herein, the term “compares unfavorably”, indicates that a comparison between two or more items, signals, etc., fails to provide such an advantageous relationship and/or that provides a disadvantageous relationship. Such an item/signal can correspond to one or more numeric values, one or more measurements, one or more counts and/or proportions, one or more types of data, and/or other information with attributes that can be compared to a threshold, to each other and/or to attributes of other information to determine whether a favorable or unfavorable comparison exists. Examples of such a advantageous relationship can include: one item/signal being greater than (or greater than or equal to) a threshold value, one item/signal being less than (or less than or equal to) a threshold value, one item/signal being greater than (or greater than or equal to) another item/signal, one item/signal being less than (or less than or equal to) another item/signal, one item/signal matching another item/signal, one item/signal substantially matching another item/signal within a predefined or industry accepted tolerance such as 1%, 5%, 10% or some other margin, etc. Furthermore, one skilled in the art will recognize that such a comparison between two items/signals can be performed in different ways. For example, when the advantageous relationship is that signal  1  has a greater magnitude than signal  2 , a favorable comparison may be achieved when the magnitude of signal  1  is greater than that of signal  2  or when the magnitude of signal  2  is less than that of signal  1 . Similarly, one skilled in the art will recognize that the comparison of the inverse or opposite of items/signals and/or other forms of mathematical or logical equivalence can likewise be used in an equivalent fashion. For example, the comparison to determine if a signal X&gt;5 is equivalent to determining if −X&lt;−5, and the comparison to determine if signal A matches signal B can likewise be performed by determining −A matches −B or not(A) matches not(B). As may be discussed herein, the determination that a particular relationship is present (either favorable or unfavorable) can be utilized to automatically trigger a particular action. Unless expressly stated to the contrary, the absence of that particular condition may be assumed to imply that the particular action will not automatically be triggered. In other examples, the determination that a particular relationship is present (either favorable or unfavorable) can be utilized as a basis or consideration to determine whether to perform one or more actions. Note that such a basis or consideration can be considered alone or in combination with one or more other bases or considerations to determine whether to perform the one or more actions. In one example where multiple bases or considerations are used to determine whether to perform one or more actions, the respective bases or considerations are given equal weight in such determination. In another example where multiple bases or considerations are used to determine whether to perform one or more actions, the respective bases or considerations are given unequal weight in such determination. 
     As may be used herein, one or more claims may include, in a specific form of this generic form, the phrase “at least one of a, b, and c” or of this generic form “at least one of a, b, or c”, with more or less elements than “a”, “b”, and “c”. In either phrasing, the phrases are to be interpreted identically. In particular, “at least one of a, b, and c” is equivalent to “at least one of a, b, or c” and shall mean a, b, and/or c. As an example, it means: “a” only, “b” only, “c” only, “a” and “b”, “a” and “c”, “b” and “c”, and/or “a”, “b”, and “c”. 
     As may also be used herein, the terms “processing module”, “processing circuit”, “processor”, “processing circuitry”, and/or “processing unit” may be a single processing device or a plurality of processing devices. Such a processing device may be a microprocessor, micro-controller, digital signal processor, microcomputer, central processing unit, field programmable gate array, programmable logic device, state machine, logic circuitry, analog circuitry, digital circuitry, and/or any device that manipulates signals (analog and/or digital) based on hard coding of the circuitry and/or operational instructions. The processing module, module, processing circuit, processing circuitry, and/or processing unit may be, or further include, memory and/or an integrated memory element, which may be a single memory device, a plurality of memory devices, and/or embedded circuitry of another processing module, module, processing circuit, processing circuitry, and/or processing unit. Such a memory device may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and/or any device that stores digital information. Note that if the processing module, module, processing circuit, processing circuitry, and/or processing unit includes more than one processing device, the processing devices may be centrally located (e.g., directly coupled together via a wired and/or wireless bus structure) or may be distributedly located (e.g., cloud computing via indirect coupling via a local area network and/or a wide area network). Further note that if the processing module, module, processing circuit, processing circuitry and/or processing unit implements one or more of its functions via a state machine, analog circuitry, digital circuitry, and/or logic circuitry, the memory and/or memory element storing the corresponding operational instructions may be embedded within, or external to, the circuitry comprising the state machine, analog circuitry, digital circuitry, and/or logic circuitry. Still further note that, the memory element may store, and the processing module, module, processing circuit, processing circuitry and/or processing unit executes, hard coded and/or operational instructions corresponding to at least some of the steps and/or functions illustrated in one or more of the Figures. Such a memory device or memory element can be included in an article of manufacture. 
     One or more embodiments have been described above with the aid of method steps illustrating the performance of specified functions and relationships thereof. The boundaries and sequence of these functional building blocks and method steps have been arbitrarily defined herein for convenience of description. Alternate boundaries and sequences can be defined so long as the specified functions and relationships are appropriately performed. Any such alternate boundaries or sequences are thus within the scope and spirit of the claims. Further, the boundaries of these functional building blocks have been arbitrarily defined for convenience of description. Alternate boundaries could be defined as long as the certain significant functions are appropriately performed. Similarly, flow diagram blocks may also have been arbitrarily defined herein to illustrate certain significant functionality. 
     To the extent used, the flow diagram block boundaries and sequence could have been defined otherwise and still perform the certain significant functionality. Such alternate definitions of both functional building blocks and flow diagram blocks and sequences are thus within the scope and spirit of the claims. One of average skill in the art will also recognize that the functional building blocks, and other illustrative blocks, modules and components herein, can be implemented as illustrated or by discrete components, application specific integrated circuits, processors executing appropriate software and the like or any combination thereof 
     In addition, a flow diagram may include a “start” and/or “continue” indication. The “start” and “continue” indications reflect that the steps presented can optionally be incorporated in or otherwise used in conjunction with one or more other routines. In addition, a flow diagram may include an “end” and/or “continue” indication. The “end” and/or “continue” indications reflect that the steps presented can end as described and shown or optionally be incorporated in or otherwise used in conjunction with one or more other routines. In this context, “start” indicates the beginning of the first step presented and may be preceded by other activities not specifically shown. Further, the “continue” indication reflects that the steps presented may be performed multiple times and/or may be succeeded by other activities not specifically shown. Further, while a flow diagram indicates a particular ordering of steps, other orderings are likewise possible provided that the principles of causality are maintained. 
     The one or more embodiments are used herein to illustrate one or more aspects, one or more features, one or more concepts, and/or one or more examples. A physical embodiment of an apparatus, an article of manufacture, a machine, and/or of a process may include one or more of the aspects, features, concepts, examples, etc. described with reference to one or more of the embodiments discussed herein. Further, from figure to figure, the embodiments may incorporate the same or similarly named functions, steps, modules, etc. that may use the same or different reference numbers and, as such, the functions, steps, modules, etc. may be the same or similar functions, steps, modules, etc. or different ones. 
     Unless specifically stated to the contra, signals to, from, and/or between elements in a figure of any of the figures presented herein may be analog or digital, continuous time or discrete time, and single-ended or differential. For instance, if a signal path is shown as a single-ended path, it also represents a differential signal path. Similarly, if a signal path is shown as a differential path, it also represents a single-ended signal path. While one or more particular architectures are described herein, other architectures can likewise be implemented that use one or more data buses not expressly shown, direct connectivity between elements, and/or indirect coupling between other elements as recognized by one of average skill in the art. 
     The term “module” is used in the description of one or more of the embodiments. A module implements one or more functions via a device such as a processor or other processing device or other hardware that may include or operate in association with a memory that stores operational instructions. A module may operate independently and/or in conjunction with software and/or firmware. As also used herein, a module may contain one or more sub-modules, each of which may be one or more modules. 
     As may further be used herein, a computer readable memory includes one or more memory elements. A memory element may be a separate memory device, multiple memory devices, or a set of memory locations within a memory device. Such a memory device may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, a quantum register or other quantum memory and/or any other device that stores data in a non-transitory manner. Furthermore, the memory device may be in a form of a solid-state memory, a hard drive memory or other disk storage, cloud memory, thumb drive, server memory, computing device memory, and/or other non-transitory medium for storing data. The storage of data includes temporary storage (i.e., data is lost when power is removed from the memory element) and/or persistent storage (i.e., data is retained when power is removed from the memory element). As used herein, a transitory medium shall mean one or more of: (a) a wired or wireless medium for the transportation of data as a signal from one computing device to another computing device for temporary storage or persistent storage; (b) a wired or wireless medium for the transportation of data as a signal within a computing device from one element of the computing device to another element of the computing device for temporary storage or persistent storage; (c) a wired or wireless medium for the transportation of data as a signal from one computing device to another computing device for processing the data by the other computing device; and (d) a wired or wireless medium for the transportation of data as a signal within a computing device from one element of the computing device to another element of the computing device for processing the data by the other element of the computing device. As may be used herein, a non-transitory computer readable memory is substantially equivalent to a computer readable memory. A non-transitory computer readable memory can also be referred to as a non-transitory computer readable storage medium. 
     One or more functions associated with the methods and/or processes described herein can be implemented via a processing module that operates via the non-human “artificial” intelligence (AI) of a machine. Examples of such AI include machines that operate via anomaly detection techniques, decision trees, association rules, expert systems and other knowledge-based systems, computer vision models, artificial neural networks, convolutional neural networks, support vector machines (SVMs), Bayesian networks, genetic algorithms, feature learning, sparse dictionary learning, preference learning, deep learning and other machine learning techniques that are trained using training data via unsupervised, semi-supervised, supervised and/or reinforcement learning, and/or other AI. The human mind is not equipped to perform such AI techniques, not only due to the complexity of these techniques, but also due to the fact that artificial intelligence, by its very definition-requires “artificial” intelligence-i.e., machine/non-human intelligence. 
     One or more functions associated with the methods and/or processes described herein can be implemented as a large-scale system that is operable to receive, transmit and/or process data on a large-scale. As used herein, a large-scale refers to a large number of data, such as one or more kilobytes, megabytes, gigabytes, terabytes or more of data that are received, transmitted and/or processed. Such receiving, transmitting and/or processing of data cannot practically be performed by the human mind on a large-scale within a reasonable period of time, such as within a second, a millisecond, microsecond, a real-time basis or other high speed required by the machines that generate the data, receive the data, convey the data, store the data and/or use the data. 
     One or more functions associated with the methods and/or processes described herein can require data to be manipulated in different ways within overlapping time spans. The human mind is not equipped to perform such different data manipulations independently, contemporaneously, in parallel, and/or on a coordinated basis within a reasonable period of time, such as within a second, a millisecond, microsecond, a real-time basis or other high speed required by the machines that generate the data, receive the data, convey the data, store the data and/or use the data. 
     One or more functions associated with the methods and/or processes described herein can be implemented in a system that is operable to electronically receive digital data via a wired or wireless communication network and/or to electronically transmit digital data via a wired or wireless communication network. Such receiving and transmitting cannot practically be performed by the human mind because the human mind is not equipped to electronically transmit or receive digital data, let alone to transmit and receive digital data via a wired or wireless communication network. 
     One or more functions associated with the methods and/or processes described herein can be implemented in a system that is operable to electronically store digital data in a memory device. Such storage cannot practically be performed by the human mind because the human mind is not equipped to electronically store digital data. 
     One or more functions associated with the methods and/or processes described herein may operate to cause an action by a processing module directly in response to a triggering event—without any intervening human interaction between the triggering event and the action. Any such actions may be identified as being performed “automatically”, “automatically based on” and/or “automatically in response to” such a triggering event. Furthermore, any such actions identified in such a fashion specifically preclude the operation of human activity with respect to these actions—even if the triggering event itself may be causally connected to a human activity of some kind. 
     While particular combinations of various functions and features of the one or more embodiments have been expressly described herein, other combinations of these features and functions are likewise possible. The present disclosure is not limited by the particular examples disclosed herein and expressly incorporates these other combinations.