Adjusting a dispersal parameter of dispersedly stored data

A method begins by a processing module storing data files utilizing a dispersed storage error coding function that includes a pillar width parameter and a decode threshold parameter. The method continues with the processing module determining whether to adjust the pillar width parameter based one or more memory performance characteristics. When the pillar width parameter is to be decreased, the method continues with the processing module identifying one or more pillars within a memory to delete to produce one or more identified pillars, identifying encoded data slices of one or more of the data files stored in the one or more identified pillars to produce identified encoded data slices, and deleting the identified encoded data slices.

Not Applicable

Not Applicable

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computing systems and more particularly to data storage solutions within such computing systems.

2. Description of Related Art

Computers are known to communicate, process, and store data. Such computers range from wireless smart phones to data centers that support millions of web searches, stock trades, or on-line purchases every day. In general, a computing system generates data and/or manipulates data from one form into another. For instance, an image sensor of the computing system generates raw picture data and, using an image compression program (e.g., JPEG, MPEG, etc.), the computing system manipulates the raw picture data into a standardized compressed image.

With continued advances in processing speed and communication speed, computers are capable of processing real time multimedia data for applications ranging from simple voice communications to streaming high definition video. As such, general-purpose information appliances are replacing purpose-built communications devices (e.g., a telephone). For example, smart phones can support telephony communications but they are also capable of text messaging and accessing the internet to perform functions including email, web browsing, remote applications access, and media communications (e.g., telephony voice, image transfer, music files, video files, real time video streaming. etc.).

Each type of computer is constructed and operates in accordance with one or more communication, processing, and storage standards. As a result of standardization and with advances in technology, more and more information content is being converted into digital formats. For example, more digital cameras are now being sold than film cameras, thus producing more digital pictures. As another example, web-based programming is becoming an alternative to over the air television broadcasts and/or cable broadcasts. As further examples, papers, books, video entertainment, home video, etc. are now being stored digitally, which increases the demand on the storage function of computers.

A typical computer storage system includes one or more memory devices aligned with the needs of the various operational aspects of the computer's processing and communication functions. Generally, the immediacy of access dictates what type of memory device is used. For example, random access memory (RAM) memory can be accessed in any random order with a constant response time, thus it is typically used for cache memory and main memory. By contrast, memory device technologies that require physical movement such as magnetic disks, tapes, and optical discs, have a variable response time as the physical movement can take longer than the data transfer, thus they are typically used for secondary memory (e.g., hard drive, backup memory, etc.).

A computer's storage system will be compliant with one or more computer storage standards that include, but are not limited to, network file system (NFS), flash file system (FFS), disk file system (DFS), small computer system interface (SCSI), internet small computer system interface (iSCSI), file transfer protocol (FTP), and web-based distributed authoring and versioning (WebDAV). These standards specify the data storage format (e.g., files, data objects, data blocks, directories, etc.) and interfacing between the computer's processing function and its storage system, which is a primary function of the computer's memory controller.

Despite the standardization of the computer and its storage system, memory devices fail; especially commercial grade memory devices that utilize technologies incorporating physical movement (e.g., a disc drive). For example, it is fairly common for a disc drive to routinely suffer from bit level corruption and to completely fail after three years of use. One solution is to a higher-grade disc drive, which adds significant cost to a computer.

Another solution is to utilize multiple levels of redundant disc drives to replicate the data into two or more copies. One such redundant drive approach is called redundant array of independent discs (RAID). In a RAID device, a RAID controller adds parity data to the original data before storing it across the array. The parity data is calculated from the original data such that the failure of a disc will not result in the loss of the original data. For example, RAID 5 uses three discs to protect data from the failure of a single disc. The parity data, and associated redundancy overhead data, reduces the storage capacity of three independent discs by one third (e.g., n−1=capacity). RAID 6 can recover from a loss of two discs and requires a minimum of four discs with a storage capacity of n−2.

While RAID addresses the memory device failure issue, it is not without its own failures issues that affect its effectiveness, efficiency and security. For instance, as more discs are added to the array, the probability of a disc failure increases, which increases the demand for maintenance. For example, when a disc fails, it needs to be manually replaced before another disc fails and the data stored in the RAID device is lost. To reduce the risk of data loss, data on a RAID device is typically copied on to one or more other RAID devices. While this addresses the loss of data issue, it raises a security issue since multiple copies of data are available, which increases the chances of unauthorized access. Further, as the amount of data being stored grows, the overhead of RAID devices becomes a non-trivial efficiency issue.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1is a schematic block diagram of a computing system10that includes one or more of a first type of user devices12, one or more of a second type of user devices14, at least one distributed storage (DS) processing unit16, at least one DS managing unit18, at least one storage integrity processing unit20, and a distributed storage network (DSN) memory22coupled via a network24. The network24may 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 memory22includes a plurality of distributed storage (DS) units36for storing data of the system. Each of the DS units36includes 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 devices12-14, the DS processing unit16, the DS managing unit18, and the storage integrity processing unit20may 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 core26and one or more interfaces30,32, and/or33. An embodiment of the computing core26will be described with reference toFIG. 2.

With respect to the interfaces, each of the interfaces30,32, and33includes software and/or hardware to support one or more communication links via the network24indirectly and/or directly. For example, interfaces30support a communication link (wired, wireless, direct, via a LAN, via the network24, etc.) between the second type of user device14and the DS processing unit16. As another example, DSN interface32supports a plurality of communication links via the network24between the DSN memory22and the DS processing unit16, the first type of user device12, and/or the storage integrity processing unit20. As yet another example, interface33supports a communication link between the DS managing unit18and any one of the other devices and/or units12,14,16,20, and/or22via the network24.

In general and with respect to data storage, the system10supports 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 unit18performs 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 unit18establishes 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 devices12-14(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 unit18coordinates the creation of a vault (e.g., a virtual memory block) within the DSN memory22for a user device (for a group of devices, or for public access). The DS managing unit18also determines the distributed data storage parameters for the vault. In particular, the DS managing unit18determines 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 module18creates and stores, locally or within the DSN memory22, 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 unit18creates billing information for a particular user, user group, vault access, public vault access, etc. For instance, the DS managing unit18tracks the number of times 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 unit18tracks 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 unit18also performs network operations, network administration, and/or network maintenance. As at least part of performing the network operations and/or administration, the DS managing unit18monitors performance of the devices and/or units of the system10for potential failures, determines the devices and/or unit's activation status, determines the devices' and/or units' loading, and any other system level operation that affects the performance level of the system10. For example, the DS managing unit18receives and aggregates network management alarms, alerts, errors, status information, performance information, and messages from the devices12-14and/or the units16,20,22. For example, the DS managing unit18receives a simple network management protocol (SNMP) message regarding the status of the DS processing unit16.

The DS managing unit18performs the network maintenance by identifying equipment within the system10that needs replacing, upgrading, repairing, and/or expanding. For example, the DS managing unit18determines that the DSN memory22needs more DS units36or that one or more of the DS units36needs updating.

The second primary function (i.e., distributed data storage and retrieval) begins and ends with a user device12-14. For instance, if a second type of user device14has a data file38and/or data block40to store in the DSN memory22, it send the data file38and/or data block40to the DS processing unit16via its interface30. As will be described in greater detail with reference toFIG. 2, the interface30functions 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 interface30may attach a user identification code (ID) to the data file38and/or data block40.

The DS processing unit16receives the data file38and/or data block40via its interface30and performs a distributed storage (DS) process34thereon (e.g., an error coding dispersal storage function). The DS processing34begins by partitioning the data file38and/or data block40into one or more data segments, which is represented as Y data segments. For example, the DS processing34may partition the data file38and/or data block40into a fixed byte size segment (e.g., 21to 2nbytes, where n=>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 processing34error 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 slices42-48, 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 slice42-48, the DS processing unit16creates a unique slice name and appends it to the corresponding slice42-48. The slice name includes universal DSN memory addressing routing information (e.g., virtual memory addresses in the DSN memory22) and user-specific information (e.g., user ID, file name, data block identifier, etc.).

The DS processing unit16transmits the plurality of EC slices42-48to a plurality of DS units36of the DSN memory22via the DSN interface32and the network24. The DSN interface32formats each of the slices for transmission via the network24. For example, the DSN interface32may utilize an internet protocol (e.g., TCP/IP, etc.) to packetize the slices42-48for transmission via the network24.

The number of DS units36receiving the slices42-48is dependent on the distributed data storage parameters established by the DS managing unit18. For example, the DS managing unit18may indicate that each slice is to be stored in a different DS unit36. As another example, the DS managing unit18may indicate that like slice numbers of different data segments are to be stored in the same DS unit36. For example, the first slice of each of the data segments is to be stored in a first DS unit36, the second slice of each of the data segments is to be stored in a second DS unit36, etc. In this manner, the data is encoded and distributedly stored at physically diverse locations to improved data storage integrity and security.

Each DS unit36that receives a slice42-48for storage translates the virtual DSN memory address of the slice into a local physical address for storage. Accordingly, each DS unit36maintains a virtual to physical memory mapping to assist in the storage and retrieval of data.

The first type of user device12performs a similar function to store data in the DSN memory22with the exception that it includes the DS processing. As such, the device12encodes and slices the data file and/or data block it has to store. The device then transmits the slices11to the DSN memory via its DSN interface32and the network24.

For a second type of user device14to retrieve a data file or data block from memory, it issues a read command via its interface30to the DS processing unit16. The DS processing unit16performs the DS processing34to identify the DS units36storing the slices of the data file and/or data block based on the read command. The DS processing unit16may also communicate with the DS managing unit18to verify that the user device14is authorized to access the requested data.

Assuming that the user device is authorized to access the requested data, the DS processing unit16issues slice read commands to at least a threshold number of the DS units36storing the requested data (e.g., to at least 10 DS units for a 16/10 error coding scheme). Each of the DS units36receiving 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 unit16.

Once the DS processing unit16has 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 unit16provides the data file38and/or data block40to the user device14. Note that the first type of user device12performs a similar process to retrieve a data file and/or data block.

The storage integrity processing unit20performs the third primary function of data storage integrity verification. In general, the storage integrity processing unit20periodically retrieves slices45, 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 unit20determines 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 unit20stores the rebuild slice, or slices, in the appropriate DS unit(s)36in a manner that mimics the write process previously described.

FIG. 2is a schematic block diagram of an embodiment of a computing core26that includes a processing module50, a memory controller52, main memory54, a video graphics processing unit55, an input/output (IO) controller56, a peripheral component interconnect (PCI) interface58, at least one IO device interface module62, 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 module66, a host bus adapter (HBA) interface module68, a network interface module70, a flash interface module72, a hard drive interface module74, and a DSN interface module76. Note the DSN interface module76and/or the network interface module70may function as the interface30of the user device14ofFIG. 1. Further note that the IO device interface module62and/or the memory interface modules may be collectively or individually referred to as IO ports.

FIG. 3is a schematic block diagram of an embodiment of a dispersed storage (DS) processing module34of user device12and/or of the DS processing unit16. The DS processing module34includes a gateway module78, an access module80, a grid module82, and a storage module84. The DS processing module34may also include an interface30and the DSnet interface32or the interfaces68and/or70may be part of user12or of the DS processing unit14. The DS processing module34may further include a bypass/feedback path between the storage module84to the gateway module78. Note that the modules78-84of the DS processing module34may be in a single unit or distributed across multiple units.

In an example of storing data, the gateway module78receives an incoming data object that includes a user ID field86, an object name field88, and the data field40and 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 module78authenticates the user associated with the data object by verifying the user ID86with the managing unit18and/or another authenticating unit.

When the user is authenticated, the gateway module78obtains user information from the management unit18, 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 units36. For example, vault1(i.e., user1's DSN memory space) includes eight DS storage units (X=8 wide) and vault2(i.e., user2'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 module78uses the user information to assign a source name35to the data. For instance, the gateway module78determines the source name35of the data object40based 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 module78may generate the file ID based on a hash function of the data object40. Note that the gateway module78may also perform 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 module80receives the data object40and creates a series of data segments1through Y90-92in 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 module82receives 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 module82error encodes (e.g., Reed-Solomon, Convolution encoding, Trellis encoding, etc.) the data segment or manipulated data segment into X error coded data slices42-44.

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 module34can 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 module82generates a unique slice name37and attaches it thereto. The slice name37includes 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 segments1-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 module82determines which of the DS storage units36will store the EC data slices based on a dispersed storage memory mapping associated with the user'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 units36is 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 unit36. Further note that EC data slices of the same pillar number but of different segments (e.g., EC data slice1of data segment1and EC data slice1of data segment2) may be stored on the same or different DS storage units36.

The storage module84performs 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 module82. The storage module84then outputs the encoded data slices1through X of each segment1through Y to the DS storage units36. Each of the DS storage units36stores 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 device12and/or14sends a read request to the DS processing unit14, which authenticates the request. When the request is authentic, the DS processing unit14sends a read message to each of the DS storage units36storing slices of the data object being read. The slices are received via the DSnet interface32and processed by the storage module84, which performs a parity check and provides the slices to the grid module82when the parity check was successful. The grid module82decodes the slices in accordance with the error coding dispersal storage function to reconstruct the data segment. The access module80reconstructs the data object from the data segments and the gateway module78formats the data object for transmission to the user device.

FIG. 4is a schematic block diagram of an embodiment of a grid module82that includes a control unit73, a pre-slice manipulator75, an encoder77, a slicer79, a post-slice manipulator81, a pre-slice de-manipulator83, a decoder85, a de-slicer87, and/or a post-slice de-manipulator89. Note that the control unit73may be partially or completely external to the grid module82. For example, the control unit73may be part of the computing core at a remote location, part of a user device, part of the DS managing unit18, or distributed amongst one or more DS storage units.

In an example of write operation, the pre-slice manipulator75receives a data segment90-92and a write instruction from an authorized user device. The pre-slice manipulator75determines if pre-manipulation of the data segment90-92is required and, if so, what type. The pre-slice manipulator75may make the determination independently or based on instructions from the control unit73, 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 manipulator75manipulates the data segment90-92in 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., CRC32), and/or other data manipulations to produce the pre-manipulated data segment.

The encoder77encodes the pre-manipulated data segment92using a forward error correction (FEC) encoder (and/or other type of erasure coding and/or error coding) to produce an encoded data segment94. The encoder77determines which forward error correction algorithm to use based on a predetermination associated with the user'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 segment92metadata, 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 encoder77may use a different encoding algorithm for each data segment92, the same encoding algorithm for the data segments92of a data object, or a combination thereof.

The encoded data segment94is of greater size than the data segment92by 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 segment92. For example, if X=16 and T=10, then the data segment92will be recoverable as long as 10 or more EC data slices per segment are not corrupted.

The slicer79transforms the encoded data segment94into EC data slices in accordance with the slicing parameter from the vault for this user and/or data segment92. For example, if the slicing parameter is X=16, then the slicer79slices each encoded data segment94into 16 encoded slices.

The post-slice manipulator81performs, if enabled, post-manipulation on the encoded slices to produce the EC data slices. If enabled, the post-slice manipulator81determines 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-manipulator89receives at least a read threshold number of EC data slices and performs the inverse function of the post-slice manipulator81to produce a plurality of encoded slices. The de-slicer87de-slices the encoded slices to produce an encoded data segment94. The decoder85performs the inverse function of the encoder77to recapture the data segment90-92. The pre-slice de-manipulator83performs the inverse function of the pre-slice manipulator75to recapture the data segment90-92.

FIG. 5is a diagram of an example of slicing an encoded data segment94by the slicer79. In this example, the encoded data segment94includes thirty-two bits, but may include more or less bits. The slicer79disperses the bits of the encoded data segment94across the EC data slices in a pattern as shown. As such, each EC data slice does not include consecutive bits of the data segment94reducing the impact of consecutive bit failures on data recovery. For example, if EC data slice2(which includes bits1,5,9,13,17,25, and29) is unavailable (e.g., lost, inaccessible, or corrupted), the data segment can be reconstructed from the other EC data slices (e.g.,1,3and4for a read threshold of 3 and a width of 4).

FIG. 6is a schematic block diagram of another embodiment of a computing system that includes one or more user devices12, a dispersed storage (DS) processing unit16, a network24, and a dispersed storage network (DSN) memory22. The user device12may include one or more of a computing core26, an interface32, a Flash memory102, and a magnetic drive memory104. The computing core26includes a DS processing34. The DS memory22includes a plurality of DS units36. The DS unit36includes one or more of the computing core26, the interface32, the Flash memory102, and the magnetic drive memory104.

The Flash memory102provides a first memory type and may be implemented utilizing non-volatile electrically erasable programmable read-only memory (EEPROM). An alternative non-volatile solid-state storage technology including one or more of static random access memory (SRAM) and dynamic random access memory (DRAM) may be utilized as a substitute for the Flash memory102. The magnetic drive memory104provides a second memory type and may be implemented utilizing a non-volatile random access memory device that includes rotating rigid platters spun by a motor, wherein the rotating rigid platters serve to magnetically store data that is written and read utilizing a read/write head that floats above the platters. Such a first memory device type and a second memory device type provide storage of data in accordance with memory storage characteristics. For example, the first memory device type provides faster access via lower access latency when implemented with Flash memory technology as compared to the second memory device type when implemented with magnetic drive memory technology. As another example, the second memory device type provides lower-cost storage on a normalized basis when implemented with the magnetic drive memory technology as compared to the first memory device type when implemented with the flash memory technology.

The DS processing34of the user device12of the one or more user devices12generates encoded data slices and facilitates storing the encoded data slices in one or more memories of the computing system. Alternatively, a DS processing unit34of the DS processing unit16generates encoded data slices and facilitates storing the encoded data slices in the one or more memories of the computing system. The memories of the computing system includes Flash memory102of each user device12of the one or more user devices12, magnetic drive memory104of each user device12of the one or more user devices12, Flash memory102of each DS unit36of the plurality of DS units36, and magnetic drive memory104of each DS unit36of the plurality of the DSN memory22.

The DS processing34facilitates the storing of the encoded data slices in the one or more memories of the computing system by selecting one or more storage locations based on a storage requirement. The storage requirement includes one or more of a security requirement, a performance requirement, a reliability requirement, a predetermination, a cost requirement, a memory availability indicator, and a memory availability requirement. For example, the DS processing34selects a local Flash memory102of an associated user device12when the performance requirement includes a very low retrieval access latency requirement. As another example, the DS processing34selects a magnetic drive memory104of a DS unit36when the cost requirement indicates a very low cost requirement and when the reliability requirement indicates a very high required reliability level. As yet another example, the DS processing34selects a set of Flash memories associated with a set of other user devices12when a set of memory availability indicators associated with the set of other user devices12compares favorably to the memory availability requirement.

In an example of operation, a DS processing34of a first user device12dispersed storage error encodes data to produce a plurality of sets of encoded data slices. The DS processing34selects a set of Flash memories associated with a set of other user devices12of the one or more user devices12. The DS processing34stores a decode threshold number (e.g., k) of encoded data slices of a set of the plurality of sets of encoded data slices in a local flash memory associated with the first user device12. The DS processing34outputs other encoded data slices of the set of the plurality of sets of encoded data slices to the set of other user devices12via the interface32and the network24for storage therein.

In another example of operation, the DS processing34of the first user device12dispersed storage error encodes data to produce the plurality of sets of encoded data slices. The DS processing34selects a set of magnetic drive memories associated with a set of DS units36of the plurality of DS units36. The DS processing34stores the decode threshold number (e.g., k) of encoded data slices of the set of the plurality of sets of encoded data slices in the local flash memory associated with the first user device12. The DS processing34outputs other encoded data slices of the set of the plurality of sets of encoded data slices to the set of DS units36via the interface32of the first user device12, the network24, the interface32of each DS unit36of the set of DS units36, and each computing core26of the set of DS units36for storage in a set of magnetic drive memories of the set of DS units36.

Alternatively, the DS processing34outputs the other encoded data slices of a set of the plurality of sets of encoded data slices via the interface32of the first user device12and the network24to the DS processing unit16. Next, the DS processing unit16dispersed storage error encodes each encoded data slice of the other encoded data slices to produce a plurality of groups of at least one set of encoded data sub-slice corresponding to each encoded data slice of the other encoded data slices. The DS processing unit16sends the plurality of groups of at least one encoded data sub-slice via the network24to a set of DS units36for storage therein. The method of operation is discussed in greater detail with reference toFIGS. 7A-12B.

FIG. 7Ais a schematic block diagram of another embodiment of a computing system that includes a computing device110, a dispersed storage (DS) processing unit16, and a dispersed storage network (DSN) memory22. The DSN memory22includes one or more of a secondary magnetic drive memory, a computing device memory, a user device memory, and at least one set of DS units. The computing device110includes a DS module112and a local memory114. The local memory114may include one or more memory devices, wherein each memory device includes one or more of a flash memory102, a magnetic drive memory104, a primary magnetic drive memory, a computing device memory, a local user device memory, a solid-state memory, and an optical memory. Alternatively, the local memory114may include memory associated with two or more computing devices110. The DS module112includes an encode data module116, a store slices module118, and an output remaining slices module120.

The encode data module116, when operable within a computing device, causes the computing device110to encode data122utilizing a dispersed storage error coding function to produce a set of encoded data slices124, wherein the dispersed storage error coding function includes a decode threshold parameter and a pillar width parameter. The encoding may further include receiving a data storage request, wherein the request includes a storage requirement including one or more of reliability, memory utilization, access latency, and security. The encode data module116further functions to encode the data122by establishing the decode threshold parameter and the pillar width parameter based on one or more of physical characteristics of the local memory and a local memory performance characteristic. The local memory performance characteristic includes one or more of memory utilization, data retrieval reliability, and data retrieval latency. The local memory physical characteristic includes one or more of a type of memory device and a number of memory devices included in the local memory114. For example, the encode data module116establishes the decode threshold parameter as 10 when the local memory114includes 10 memory devices. As another example, the encode data module116establishes the decode threshold parameter as 5 and the pillar width parameter as 21 when the local memory114includes three memory devices and a local memory performance characteristic indicates a below average data retrieval reliability level.

The store slices module118, when operable within the computing device, causes the computing device to store a number of encoded data slices126of the set of encoded data slices124in the local memory114, wherein the number is based on the decode threshold parameter and is less than the pillar width parameter. The storing may include selecting the number of encoded data slices126and writing each of the number of encoded data slices126to the local memory114. The store slices module118, when operable within the computing device110, further causes the computing device110to determine the number of encoded data slices126by at least one of performing a mathematical function on the decode threshold parameter and performing a second mathematical function based on at least one of physical structure of the local memory and performance characteristics of the local memory114. For example, the store slices module118determines the number of encoded data slices126to be the decode threshold parameter when a physical structure of the local memory indicates that more than a decode threshold parameter number of memory devices are available. As another example, the store slices module118determines the number of encoded data slices126to be the decode threshold parameter minus two when a performance characteristic of the local memory114indicates below average performance. As yet another example, the store slices module118determines the number of encoded data slices126to be the decode threshold parameter plus three when a physical structure of the local memory114indicates that less than a decode threshold parameter number of memory devices are available.

The encode data module116, when operable within the computing device110, further causes the computing device110to encode the data utilizing the dispersed storage error coding function to produce a plurality of sets of encoded data slices, which includes the set of encoded data slices. The store slices module118, when operable within the computing device110, further causes the computing device110to determine, in accordance with a set storage protocol, the number of encoded data slices of one or more sets of the plurality of sets of encoded data slices. For example, the store slices module118determines a common number of encoded data slices for each set of the plurality of sets of encoded data slices when a set storage protocol indicates to utilize a common number. As another example, the store slices module118determines a unique number of encoded data slices for each set of the plurality of sets of encoded data slices when a set storage protocol indicates to utilize a unique number for each set of encoded data slices.

The store slices module118further functions to store the number of encoded data slices126by selecting the number of encoded data slices126from the set of encoded data slices124based on the dispersed storage error coding function and issuing a number of write requests to the local memory114for the number of encoded data slices126. For example, the store slices module118selects the number of encoded data slices126aligned with subsequent decoding of the decode threshold parameter number of encoded data slices to improve recovery latency time. For instance, the store slices module118selects the number of encoded data slices associated with a first decode threshold parameter number of pillars when a unity matrix is used within a generator matrix of the dispersed storage error coding function.

The output remaining slices module120, when operable within the computing device110, causes the computing device110to output remaining encoded data slices128of the set of encoded data slices124to the DSN memory22. The outputting may include selecting the remaining encoded data slices128(e.g., pillar width-number) and sending the remaining encoded data slices128to the DSN memory22. The output remaining slices module120further functions to output the remaining encoded data slices128by sending the remaining encoded data slices128to the DS processing unit16; or (e.g., the DS processing unit16directly stores slices or encodes new slices for storage in the DSN memory22) sending the data122and the number to the DS processing unit16, wherein the DS processing unit16encodes the data122utilizing the dispersed storage error coding function to produce another set of encoded data slices, identifies the remaining encoded data slices128from the other set of encoded data slices based on the number and the a set by set basis, for the plurality, or for groupings of the plurality, and outputs the remaining encoded data slices128to the DSN memory22; and updating an encoded data slice mapping. The updating of the encoded data slice mapping includes listing identities of one or more of the remaining encoded data slices128, a DSN source name received from the DS processing unit16, and a corresponding identity of the DS processing unit16.

The outputting remaining encoded data slices128further includes one or more of selecting a memory of the DSN memory22based on one or more DSN memory performance characteristics (e.g., DSN memory utilization, DSN memory data retrieval reliability, DSN memory data retrieval latency; selecting further includes selecting based on at least one of a security requirement, a predetermination, and a message), sending a write encoded data slice request to the at least one memory for each encoded data slice of the remaining encoded data slices128, wherein each write encoded data slice request includes a corresponding encoded data slice of the remaining encoded data slices128, and updating an encoded data slice mapping. (e.g., list identities of the remaining encoded data slices128and corresponding identities of the selected at least one memory)

FIG. 7Bis a flowchart illustrating an example of storing data. The method begins at step130where a processing module (e.g., of a computing device) encodes data utilizing a dispersed storage error coding function to produce a set of encoded data slices, wherein the dispersed storage error coding function includes a decode threshold parameter and a pillar width parameter. The encoding the data further includes establishing the decode threshold parameter and the pillar width parameter based on one or more of physical characteristics of the local memory and a local memory performance characteristic. Alternatively, or in addition to, the processing module encodes the data utilizing the dispersed storage error coding function to produce a plurality of sets of encoded data slices, which includes the set of encoded data slices.

The method continues at step132where the processing module determines the number of encoded data slices by at least one of performing a mathematical function on the decode threshold parameter and performing a second mathematical function based on at least one of physical structure of the local memory and performance characteristics of the local memory. Alternatively, or in addition to, the processing module determines, in accordance with a set storage protocol, the number of encoded data slices of one or more sets of the plurality of sets of encoded data slices when the data is encoded to produce the plurality of sets of encoded data slices.

The method continues at step134where the processing module stores a number of encoded data slices of the set of encoded data slices in a local memory, wherein the number is based on the decode threshold parameter and is less than the pillar width parameter. The storing the number of encoded data slices further includes selecting the number of encoded data slices from the set of encoded data slices based on the dispersed storage error coding function and issuing a number of write requests to the local memory for the number of encoded data slices.

The method continues at step136where the processing module outputs remaining encoded data slices of the set of encoded data slices to dispersed storage network (DSN) memory. The outputting remaining encoded data slices further includes sending the remaining encoded data slices to a dispersed storage processing unit or sending the data and the number to a dispersed storage (DS) processing unit, wherein the DS processing unit encodes the data utilizing the dispersed storage error coding function to produce another set of encoded data slices, identifying the remaining encoded data slices from the other set of encoded data slices based on the number and the a set by set basis, for the plurality, or for groupings of the plurality and outputting the remaining encoded data slices to the DSN memory; and updating an encoded data slice mapping. The outputting remaining encoded data slices further includes one or more of selecting a memory of the DSN memory based on one or more DSN memory performance characteristics, sending a write encoded data slice request to the at least one memory for each encoded data slice of the remaining encoded data slices, wherein each write encoded data slice request includes a corresponding encoded data slice of the remaining encoded data slices, and updating an encoded data slice mapping.

FIG. 7Cis a schematic block diagram of another embodiment of a computing system that includes a computing device140, a dispersed storage (DS) processing unit16, and a dispersed storage network (DSN) memory22. The DSN memory22includes one or more of a secondary magnetic drive memory, a computing device memory, a user device memory, and at least one set of DS units. The computing device140includes a DS module142and a local memory114. The local memory114may include one or more memory devices, wherein each memory device includes one or more of a flash memory102, a magnetic drive memory104, a primary magnetic drive memory, a computing device memory, a local user device memory, a solid-state memory, and an optical memory. Alternatively, the local memory114may include memory associated with two or more computing devices140. The DS module142includes a receive request module144, an issue local requests module146, receive local slices module148, an issue DSN requests module150, and a decode slices module152. The receive request module144, when operable within the computing device140, causes the computing device140to receive a retrieval request154for data122, wherein the data122is encoded utilizing a dispersed storage error coding function to produce a set of encoded data slices124, wherein a number of encoded data slices126of the set of encoded data slices124are stored in the local memory114and remaining encoded data slices128of the set of encoded data slices124are stored in the DSN memory22.

The issue local requests module146, when operable within the computing device140, causes the computing device140to issue a number of data read requests156to the local memory114for retrieval of the number of encoded data slices126. The issue local requests module146functions to issue the number of data read requests156by determining the number of data read requests156by at least one of performing a number look up operation (e.g., from a previous storage sequence), performing a mathematical function on a decode threshold parameter, and performing a second mathematical function based on at least one of physical structure of the local memory and performance characteristics of the local memory, wherein the dispersed storage error coding function includes a decode threshold parameter and a pillar width parameter.

The receive local slices module148, when operable within the computing device140, causes the computing device140to determine whether a decode threshold number of encoded data slices have been received from the local memory114. The receive local slices module148functions to determine whether a decode threshold number of encoded data slices have been received by one of determining that the decode threshold number of encoded data slices have not been received when the number of data read requests156is less than a decode threshold parameter and when the number of data read requests156is greater than or equal to the decode threshold parameter decode threshold, determining whether the decode threshold number of encoded data slices have been received within a given time frame.

When the decode threshold number of encoded data slices have not been received (e.g., within a time period) from the local memory114, the issue DSN requests module150, when operable within the computing device140, causes the computing device140to issue one or more data read requests158to the DSN memory22(e.g., directly to the DSN memory22or via the DS processing unit16) for retrieving one or more of the remaining encoded data slices128. The issue DSN requests module150functions to issue the one or more data read requests158to the DSN memory22by selecting the one or more of the remaining encoded data slices128based on one or more of an encoded data slice mapping retrieval, a query, a message, and the data retrieval request. In addition, the issue DSN requests module150sends the one or more data read requests158to the DSN memory22. When the decode threshold number of encoded data slices have been received (e.g., directly from the DSN memory22to the decode slices module152or via the DS processing unit16), the decode slices module152, when operable within the computing device140, causes the computing device140to decode the decode threshold number of encoded data slices using the dispersed storage error coding function to reproduce the data122.

FIG. 7Dis a flowchart illustrating an example of retrieving data. The method begins at step160where a processing module (e.g., of a computing device) receives a retrieval request for data, wherein the data is encoded utilizing a dispersed storage error coding function to produce a set of encoded data slices, wherein a number of encoded data slices of the set of encoded data slices are stored in a local memory and remaining encoded data slices of the set of encoded data slices are stored in dispersed storage network (DSN) memory.

The method continues at step162where the processing module issues a number of data read requests to the local memory for retrieval of the number of encoded data slices. The issuing the number of data read requests includes determining the number of data read requests by at least one of performing a number look up operation, performing a mathematical function on a decode threshold parameter, and performing a second mathematical function based on at least one of physical structure of the local memory and performance characteristics of the local memory, wherein the dispersed storage error coding function includes a decode threshold parameter and a pillar width parameter.

The method continues at step164where the processing module determines whether a decode threshold number of encoded data slices have been received from the local memory. The determining whether a decode threshold number of encoded data slices have been received includes one of determining that the decode threshold number of encoded data slices have not been received when the number of data read requests is less than a decode threshold parameter and when the number of data read requests is greater than or equal to the decode threshold parameter decode threshold, determining whether the decode threshold number of encoded data slices have been received within a given time frame. The method branches to step168when the processing module determines that the decode threshold number of encoded data slices have been received. The method continues to step166when the processing module determines that the decode threshold number of encoded data slices have not been received (e.g., within a given time period).

The method continues at step166where the processing module issues one or more data read requests to the DSN memory for retrieving one or more of the remaining encoded data slices. The issuing the one or more data read requests to the DSN memory includes selecting the one or more of the remaining encoded data slices based on one or more of an encoded data slice mapping retrieval, a query, a message, and the data retrieval request. When the decode threshold number of encoded data slices have been received, the method continues at step168where the processing module decodes the decode threshold number of encoded data slices using the dispersed storage error coding function to reproduce the data.

FIG. 8Ais a schematic block diagram of another embodiment of a computing system that includes a computing device170and a dispersed storage network (DSN) memory22. The DSN memory22includes one or more of a secondary magnetic drive memory, a computing device memory, a user device memory, and at least one set of DS units. The computing device170includes a DS module172and a local memory174. The local memory174may include one or more memory devices, wherein each memory device includes one or more of a flash memory102, a magnetic drive memory104, a primary magnetic drive memory, a computing device memory, a local user device memory, a solid-state memory, and an optical memory. The DS module172includes a store data files module176, a determine pillar adjustment module178, and a contract pillars module180.

The store data files module176, when operable within the computing device170, causes the computing device170to store data files182utilizing a dispersed storage error coding function, wherein a data file of the data files is encoded using the dispersed storage error coding function to produce a plurality of sets of encoded data slices184, wherein the plurality of sets of encoded data slices184is stored in memory, and wherein the dispersed storage error coding function includes a pillar width parameter and a decode threshold parameter, where the pillar width parameter is at least 1.8 times the decode threshold parameter (e.g., a pillar width parameter of 100 and a decode threshold parameter of 10). The memory includes one or more of the local memory174and the DSN memory22. The store data files module176, when operable within the computing device170, further causes the computing device170to encode a subsequent data file utilizing a decreased pillar width parameter186(e.g., 60), the decode threshold parameter, and the dispersed storage error coding function to produce a subsequent plurality of sets of encoded data slices and store the subsequent plurality of sets of encoded data slices in the memory.

The determine pillar adjustment module178, when operable within the computing device170, causes the computing device170to determine whether to adjust the pillar width parameter based one or more memory performance characteristics188(e.g., availability and/or reliability). The determine pillar adjustment module178functions to determine to decrease the pillar width parameter by determining a memory utilization indicator associated with the memory (e.g., includes obtaining the memory utilization indicator based on one or more of a lookup, a query, a test, and receiving a message), determining a memory reliability indicator associated with the memory, and when the memory utilization indicator is unfavorable and the memory reliability indicator is favorable, indicating a decrease of the pillar width parameter. The memory utilization indicator includes one or more of an amount of available memory, an amount of utilized memory, available memory percentage of memory capacity, and utilized memory percentage of memory capacity. The memory reliability indicator includes one or more of an access latency level of the local memory, a rebuilding frequency indicator, and a data retrieval reliability level of the memory. For example, the determine pillar adjustment module178decreases the pillar width parameter from 100 to 60 when an amount of utilized memory is greater than a memory threshold and a data retrieval reliability level compares favorably to a reliability threshold.

When the pillar width parameter is to be decreased, the contract pillars module180, when operable within the computing device170, causes the computing device170to identify one or more pillars within the memory to delete to produce one or more identified pillars (e.g., and produce the decreased pillar width parameter186), identify encoded data slices of one or more of the data files stored in the one or more identified pillars to produce identified encoded data slices, and delete the identified encoded data slices (e.g., by sending delete encoded data slice requests190to the DSN memory22with regards to the identified encoded data slices). The contract pillars module180functions to identify the one or more pillars within the memory to delete by determining an amount of memory space to reclaim based on at least one of a memory utilization indicator and a memory reliability indicator, identifying one or more of the data files based on data file criteria (e.g., user identifier, minimum file size, a file priority indicator), and determining a number of pillars to be deleted based on the amount of memory space to reclaim and the identified one or more of the data files. For example, the contract pillars module180identifies pillars61-100to delete corresponding to 50 data files associated with a lower than average file priority indicator value to reclaim 100 GB of memory space.

The contract pillars module180functions to delete the identified encoded data slices by reclaiming memory space of the deleted encoded data slices and updating pillar mapping of the memory in accordance with the decreasing of the pillar width parameter and the reclaimed memory space (e.g., reassign slice name ranges per memory). The contract pillars module180functions to identify the encoded data slices by identifying the one or more of the data files (e.g., based on file priority) and for each of the one or more identified data files determining which of the encoded data slices of a respective plurality of sets of encoded data slices are stored in the one or more identified pillars to produce data file specific encoded data slices, wherein the identified encoded data slices includes the data file specific encoded data slices for each of the one or more identified data files.

FIG. 8Bis a flowchart illustrating an example of contracting data storage. The method begins at step200where a processing module (e.g., of a computing device) stores data files utilizing a dispersed storage error coding function, wherein a data file of the data files is encoded using the dispersed storage error coding function to produce a plurality of sets of encoded data slices, wherein the plurality of sets of encoded data slices is stored in memory, and wherein the dispersed storage error coding function includes a pillar width parameter and a decode threshold parameter, where the pillar width parameter is at least 1.8 times the decode threshold parameter. The memory includes one or more of a local memory and a dispersed storage network (DSN) memory. Alternatively, or in addition to, processing module encodes a subsequent data file utilizing the decreased pillar width parameter, the decode threshold parameter, and the dispersed storage error coding function to produce a subsequent plurality of sets of encoded data slices and stores the subsequent plurality of sets of encoded data slices in the memory.

The method continues at step202where the processing module determines whether to adjust the pillar width parameter based on one or more memory performance characteristics. The determining to decrease the pillar width parameter includes determining a memory utilization indicator associated with the memory, determining a memory reliability indicator associated with the memory, and when the memory utilization indicator is unfavorable and the memory reliability indicator is favorable, indicating a decrease of the pillar width parameter.

When the pillar width parameter is to be decreased, the method continues at step204where the processing module identifies one or more pillars within the memory to delete to produce one or more identified pillars. The identifying one or more pillars within the memory to delete includes determining an amount of memory space to reclaim based on at least one of a memory utilization indicator and a memory reliability indicator, identifying one or more of the data files based on data file criteria, and determining a number of pillars to be deleted based on the amount of memory space to reclaim and the identified one or more of the data files.

The method continues at step206where the processing module identifies encoded data slices of one or more of the data files stored in the one or more identified pillars to produce identified encoded data slices. The identifying encoded data slices includes identifying the one or more of the data files and for each of the one or more identified data files, determining which of the encoded data slices of a respective plurality of sets of encoded data slices are stored in the one or more identified pillars to produce data file specific encoded data slices, wherein the identified encoded data slices includes the data file specific encoded data slices for each of the one or more identified data files.

The method continues at step208where the processing module deletes the identified encoded data slices. The deleting the identified encoded data slices includes reclaiming memory space of the deleted encoded data slices and updating pillar mapping of the memory in accordance with the decreasing of the pillar width parameter and the reclaimed memory space.

FIG. 9Ais a schematic block diagram of another embodiment of a computing system that includes a computing device220and a dispersed storage network (DSN) memory22. The DSN memory22includes one or more of a secondary magnetic drive memory, a computing device memory, a user device memory, and at least one set of DS units. The computing device220includes a DS module222and a local memory174. The local memory174may include one or more memory devices, wherein each memory device includes one or more of a flash memory102, a magnetic drive memory104, a primary magnetic drive memory, a computing device memory, a local user device memory, a solid-state memory, and an optical memory. The DS module222includes a store data files module224, a determine pillar adjustment module226, and an expand pillars module228.

The store data files module224, when operable within a computing device220, causes the computing device220to store data files182utilizing a dispersed storage error coding function, wherein a data file of the data files is encoded using the dispersed storage error coding function to produce a plurality of sets of encoded data slices184, wherein the plurality of sets of encoded data slices is stored in memory, and wherein the dispersed storage error coding function includes a pillar width parameter and a decode threshold parameter, where the pillar width parameter is greater than the decode threshold parameter (e.g., a pillar width parameter of 20 and a decode threshold parameter of 10). The memory includes one or more of the local memory174and a DSN memory22. The store data files module224, when operable within the computing device220, further causes the computing device220to encode a subsequent data file utilizing an increased pillar width parameter230(e.g., 60), the decode threshold parameter, and the dispersed storage error coding function to produce a subsequent plurality of sets of encoded data slices and store the subsequent plurality of sets of encoded data slices in the memory.

The determine pillars adjustment module226, when operable within the computing device220, causes the computing device220to determine whether to adjust the pillar width parameter based one or more memory performance characteristics188(e.g., memory availability and/or memory reliability). The determine pillar adjustment module226, when operable within the computing device220, further causes the computing device220to determine to increase the pillar width parameter by one or more of determining a memory utilization indicator associated with the memory, determining a memory reliability indicator associated with the memory, and when the memory utilization indicator is favorable and the memory reliability indicator is unfavorable, indicating an increase of the pillar width parameter. The memory utilization indicator includes one or more of an amount of available memory, an amount of utilized memory, available memory percentage of memory capacity, and utilized memory percentage of memory capacity. The memory reliability indicator includes one or more of an access latency level of the local memory, a rebuilding frequency indicator, and a data retrieval reliability level of the memory. For example, the determine pillar adjustment module226increases the pillar width parameter from 20 to 60 when an amount of utilized memory is less than a memory threshold and a data retrieval reliability level compares unfavorably to a reliability threshold.

When the pillar width parameter is to be increased, the expand pillars module228, when operable within the computing device220, causes the computing device220to determine a number of additional pillars to produce the increased pillar width parameter230, identify one or more of the data files based on data file criteria (e.g., by a user identifier, a priority indicator), and for each of the one or more data files encode a data file of the one or more data files utilizing the increased pillar width parameter, the decode threshold parameter, and the dispersed storage error coding function to produce a plurality of subsets of encoded data slices232relating to the number of additional pillars (e.g., retrieve data from a decode threshold number of slices, and use new rows of an extended generator matrix to produce the plurality of subsets of encoded data slices), and store the plurality of subsets of encoded data slices232in the memory corresponding to the additional pillars.

The expand pillars module228, when operable within the computing device, further causes the computing device to determine the number of additional pillars by one or more of determining a level of unfavorability of the memory reliability indicator and determining the number of additional pillars based on the level of unfavorability. For example, the expand pillars module228determines 40 additional pillars (e.g.,21-60) when a level of memory reliability is much lower than a low reliability threshold. The expand pillars module228further functions to store the plurality of subsets of encoded data slices232by updating pillar mapping of the memory in accordance with the increasing of the pillar width parameter (e.g., wider slice name range assigned to memory).

FIG. 9Bis a flowchart illustrating an example of expanding data storage. The method begins at step240where a processing module (e.g., of a computing device) stores data files utilizing a dispersed storage error coding function, wherein a data file of the data files is encoded using the dispersed storage error coding function to produce a plurality of sets of encoded data slices, wherein the plurality of sets of encoded data slices is stored in memory, and wherein the dispersed storage error coding function includes a pillar width parameter and a decode threshold parameter, where the pillar width parameter is greater than the decode threshold parameter. The memory includes one or more of a local memory and a dispersed storage network (DSN) memory. Alternatively, or in addition to, the processing module encodes a subsequent data file utilizing an increased pillar width parameter, the decode threshold parameter, and the dispersed storage error coding function to produce a subsequent plurality of sets of encoded data slices and stores the subsequent plurality of sets of encoded data slices in the memory.

The method continues at step242where the processing module determines whether to adjust the pillar width parameter based one or more memory performance characteristics (e.g., memory availability and/or memory reliability). The determining to increase the pillar width parameter includes determining a memory utilization indicator associated with the memory, determining a memory reliability indicator associated with the memory, and when the memory utilization indicator is favorable and the memory reliability indicator is unfavorable, indicating an increase of the pillar width parameter.

When the pillar width parameter is to be increased, the method continues at step244where the processing module determines a number of additional pillars to produce an increased pillar width parameter. The determining the number of additional pillars includes determining a level of unfavorability of the memory reliability indicator and determining the number of additional pillars based on the level of unfavorability. The method continues at step246where the processing module identifies one or more of the data files based on data file criteria (e.g., based on a user identifier, a priority indicator). For example, the processing module identifies 1000 data files that are associated with a high priority indicator associated with a requirement for high data retrieval reliability.

For each of the one or more data files, the method continues at step248where the processing module encodes a data file of the one or more data files utilizing the increased pillar width parameter, the decode threshold parameter, and the dispersed storage error coding function to produce a plurality of subsets of encoded data slices relating to the number of additional pillars (e.g., retrieve data from a decode threshold number of encoded data slices retrieved from the memory, matrix multiply the data by new rows of an extended generator matrix to produce the plurality of subsets of encoded data slices). The method continues at step250where the processing module stores the plurality of subsets of encoded data slices in the memory corresponding to the additional pillars. The storing the plurality of subsets of encoded data slices includes updating pillar mapping of the memory in accordance with the increasing of the pillar width parameter (e.g., wider slice name range assigned to memory).

FIG. 10Ais a schematic block diagram of another embodiment of a computing system that includes a computing device260, a local area network (LAN)262, and a wide area network (WAN)264. The WAN264includes a dispersed storage network (DSN) memory22. The DSN memory22includes one or more of a secondary magnetic drive memory, a computing device memory, a user device memory, and at least one set of DS units. The LAN262includes a plurality of mobile device memories266and a plurality of fixed device memories268. The fixed device memory268is substantially permanently associated with the LAN262whereas the mobile device memory266may become disassociated with the LAN262from time to time. For example, a first mobile device memory266includes a smart phone that is utilized in association with the LAN262when the first mobile device266is proximally associated with a LAN262. As another example, a first fixed device memory268is associated with a cable set-top box of a home based LAN262. The mobile device memory266and the fixed device memory268may include one or more memory devices, wherein each memory device includes one or more of a flash memory102, a magnetic drive memory104, a primary magnetic drive memory, a computing device memory, a local device memory, a solid-state memory, and an optical memory.

The mobile device memory266includes mobile device available memory266when at least some of the one or more memory devices associated with the mobile device memory266are available for storage access. The fixed device memory268includes fixed device available memory268when at least some of the one or more memory devices associated with the fixed device memory268are available for storage access. The computing device260includes a dispersed storage (DS) module270and may include one or more of the mobile device memory266and the fixed device memory268. The DS module270includes an encode module272, a select LAN width module274, a select WAN width module276, a receive request module278, a request LAN slices module280, a decode module282, and a request WAN slices module284.

The encode module272, when operable within the computing device260, causes the computing device260to encode, in accordance with a dispersed storage error coding function, data286based on a decode threshold parameter and a pillar width parameter to produce a set of encoded data slices288. The encode module272further functions to encode the data286by determining the decode threshold parameter based on a minimum quantity of the fixed device available memory268and determining the pillar width parameter based on the minimum quantity of the fixed device available memory268and a minimum quantity of the mobile device available memory266. For example, the encode module272determines the decode threshold parameter to be 3 when a quantity of the fixed device available memory268is 3 fixed devices268. As another example, the encode module272determines the decode threshold parameter to be 10 when a quantity of the fixed device available memory268is 15 fixed devices268and a decode threshold parameter minimum number is 10. As yet another example, the encode module272determines the pillar width parameter to be 5 when the quantity of the fixed device available memory268is 3 fixed devices268and a quantity of the mobile device available memory266is 3. As a still further example, the encode module272determines the pillar width parameter to be 16 when the quantity of the fixed device available memory268is 15 fixed devices268, a quantity of the mobile device available memory266is 12, and a pillar width parameter minimum number is 16.

The select LAN width module274, when operable within the computing device260, causes the computing device260to select a local area network (LAN) pillar width value of encoded data slices290of the set of encoded data slices288for storage in LAN available memories (e.g., available mobile device memories266and/or available fixed device memories268), wherein the LAN pillar width value is based on the decode threshold parameter, the pillar width parameter, and quantities of the LAN available memories and wherein the LAN pillar width value is equal to or greater than a value of the decode threshold parameter. The LAN available memories includes mobile device available memory266and fixed device available memory268. The select LAN width module274may select the LAN pillar width value as less than a value of the pillar width parameter. For example the select LAN width module274selects a LAN pillar width value of 12 when the pillar width parameter is 16.

The select WAN width module276, when operable within the computing device260, causes the computing device260to select a wide area network (WAN) pillar width value of encoded data slices292of the set of encode data slices288for storage in the DSN memory22of the wide area network264, wherein the WAN pillar width value is based on the decode threshold parameter and the pillar width parameter and wherein the WAN pillar width value is equal to or greater than the value of the decode threshold parameter. The select WAN width module276may select the WAN pillar width value as less than a value of the pillar width parameter. For example the select WAN width module276selects a WAN pillar width value of 12 when the pillar width parameter is 16.

The receive request module278, when operable within the computing device260, causes the computing device260to receive a request294to retrieve the data286. The request LAN slices module280, when operable within the computing device260, causes the computing device260to determine whether the LAN is accessible (e.g., based on a query to one or more mobile device memories266and/or one or more fixed device memories268), and when the LAN is accessible, request the LAN pillar width value of encoded data slices from the LAN memories (e.g., sending LAN slices requests296to the LAN memories). For example, the request LAN slices module280sends 12 LAN slice requests296to the LAN memories when a LAN pillar width value is 12.

The decode module282, when operable within the computing device260, causes the computing device260to, when at least a decode threshold parameter of the LAN pillar width value of encoded data slices290have been received, decode, in accordance with the dispersed storage error coding function to produce the data286. The request WAN slices module284, when operable within the computing device260, causes the computing device260to, when the at least the decode threshold parameter of the LAN pillar width value of encoded data slices have not been received, request at least one of the WAN pillar width value of encoded data slices292from the DSN memory22(e.g., via at least one WAN slice request298). For example, the request WAN slices module284sends three WAN slice requests298to the DSN memory22when the decode threshold parameter is 10 and 7 LAN slices290have been received. When the LAN262is not accessible, the request WAN slices module284requests the WAN pillar width value of encoded data slices292from the DSN memory22. For example, the request WAN slices module284sends 12 WAN slice requests298to the DSN memory22when the LAN262is not accessible.

FIG. 10Bis a flowchart illustrating an example of accessing data. The method begins at step300where a processing module (e.g., of a computing device) encodes, in accordance with a dispersed storage error coding function, data based on a decode threshold parameter and a pillar width parameter to produce a set of encoded data slices. The encoding the data includes determining the decode threshold parameter based on a minimum quantity of the fixed device available memory and determining the pillar width parameter based on the minimum quantity of the fixed device available memory and a minimum quantity of the mobile device available memory.

The method continues at step302where the processing module selects a local area network (LAN) pillar width value of encoded data slices of the set of encoded data slices for storage in LAN available memories, wherein the LAN pillar width value is based on the decode threshold parameter, the pillar width parameter, and quantities of the LAN available memories and wherein the LAN pillar width value is equal to or greater than a value of the decode threshold parameter. The LAN available memories includes mobile device available memory and fixed device available memory. The LAN pillar width value may be less than a value of the pillar width parameter to provide data retrieval capability without utilizing LAN memories to store all the slices.

The method continues at step304where the processing module selects a wide area network (WAN) pillar width value of encoded data slices of the set of encode data slices for storage in a dispersed storage network (DSN) memory of a wide area network, wherein the WAN pillar width value is based on the decode threshold parameter and the pillar width parameter and wherein the WAN pillar width value is equal to or greater than the value of the decode threshold parameter. The WAN pillar width value may be less than a value of the pillar width parameter to provide data retrieval capability without utilizing the DSN memory to store all the slices.

The method continues at step306where the processing module receives a request to retrieve the data. The method continues at step308where the processing module determines whether the LAN is accessible. For example, the processing module initiates a query to a memory device associated with the LAN. The method branches to step312when the processing module determines that the LAN is accessible. The method continues to step310when the processing module determines that the LAN is not accessible. The method continues at step310where the processing module requests the WAN pillar width value of encoded data slices from the DSN memory when the LAN is not accessible. The method branches to step316.

The method continues at step312where the processing module requests the LAN pillar width value of encoded data slices from the LAN memories when the LAN is accessible. When the at least the decode threshold parameter of the LAN pillar width value of encoded data slices have not been received, the method continues at step314where the processing module requests at least one (e.g., enough to provide a decode threshold number of encoded data slices) of the WAN pillar width value of encoded data slices from the DSN memory. The method continues at step316, when at least a decode threshold parameter of the LAN pillar width value of encoded data slices have been received, where the processing module decodes, in accordance with the dispersed storage error coding function to produce the data.

FIG. 10Cis a schematic block diagram of another embodiment of a computing system that includes a computing device320, a local area network (LAN)262, and a wide area network (WAN)264. The WAN264includes a dispersed storage network (DSN) memory22. The DSN memory22includes one or more of a secondary magnetic drive memory, a computing device memory, a user device memory, and at least one set of DS units. The LAN262includes a plurality of mobile device memories266and a plurality of fixed device memories268. For example, a laptop computer includes a mobile device memory266. As another example, desktop computer includes a fixed device memory268. The mobile device memory266and the fixed device memory268may include one or more memory devices, wherein each memory device includes one or more of a flash memory102, a magnetic drive memory104, a primary magnetic drive memory, a computing device memory, a local device memory, a solid-state memory, and an optical memory.

The mobile device memory266includes mobile device available memory266when at least some of the one or more memory devices associated with the mobile device memory266are available for storage access. The fixed device memory268includes fixed device available memory268when at least some of the one or more memory devices associated with the fixed device memory268are available for storage access. The computing device320includes a dispersed storage (DS) module322and may include one or more of the mobile device memory266and the fixed device memory268. The DS module322functions to set up the LAN262and WAN264and includes a determine LAN memories module324, an establish parameters module326, a determine LAN pillar width module328, and a determine WAN pillar width module330.

The determine LAN memories module324, when operable within the computing device320, causes the computing device320to determine LAN available memories of the LAN262environment. The determine LAN memories module324functions to determine the LAN available memories by identifying one or more mobile device available memories266and identifying one or more fixed device available memories268. For example, the determine LAN memories module324sends an availability request332to one or more mobile device memories266and one or more fixed device memories268and receives availability responses334which identifies LAN available memories.

The establish parameters module326, when operable within the computing device320, causes the computing device320to establish a decode threshold parameter336and a pillar width parameter338of a dispersed storage error coding function based on quantities of the LAN available memories. The establish parameters module326functions to establish the decode threshold parameter336and the pillar width parameter338by determining the decode threshold parameter336based on a minimum quantity of the fixed device available memory and determining the pillar width parameter338based on the minimum quantity of the fixed device available memory and a minimum quantity of the mobile device available memory. For example, the establish parameters module326establishes a decode threshold parameter336to be 10 and a pillar width parameter338to be 16 when a minimum quantity of the fixed device available memory is 10, eight mobile device memories266are available, and 12 fixed device memories268are available.

The determine LAN pillar width module328, when operable within the computing device320, causes the computing device320to determine a LAN pillar width value340based on the decode threshold parameter336, the pillar width parameter338, and the quantities of the LAN available memories, wherein the LAN pillar width value340is equal to or greater than a value of the decode threshold parameter336. The determine LAN pillar width module328is further operable to determine the LAN pillar width value340to be less than a value of the pillar width parameter338. For example, the determine LAN pillar width module328determines a LAN pillar width value340to be 12 when the decode threshold parameter336is 10, the pillar width parameter338is 16, and there are greater than 12 LAN available memories.

The determine WAN pillar width module330, when operable within the computing device320, causes the computing device320to determine a WAN pillar width value342based on the decode threshold parameter336and the pillar width parameter338, wherein the WAN pillar width value342is equal to or greater than the value of the decode threshold parameter336, wherein, for data that is encoded into a set of encoded data slices in accordance with the dispersed storage error coding function, the decode threshold parameter336, and the pillar width parameter338, a LAN pillar width value340of encoded data slices of the set of encoded data slices are selected for storage in the LAN available memories, and a WAN pillar width value342of encoded data slices of the set of encode data slices for storage in the DSN memory22of the WAN264. The determine WAN pillar width module330is further operable to determine the WAN pillar width value342to be less than the value of the pillar width parameter338. For example, the determine WAN pillar width module330determines a WAN pillar width value342to be 11 when the decode threshold parameter336is 10 and the pillar width parameter338is 16.

FIG. 10Dis a flowchart illustrating an example of setting up a dispersed storage system. The method begins at step350where a processing module (e.g., of a computing device) determines LAN available memories of a local area network (LAN) environment. The determining LAN available memories includes identifying one or more mobile device available memories and identifying one or more fixed device available memories. The method continues at step352where the processing module establishes a decode threshold parameter and a pillar width parameter of a dispersed storage error coding function based on quantities of the LAN available memories. The establishing the decode threshold parameter and the pillar width parameter includes determining the decode threshold parameter based on a minimum quantity of the fixed device available memory and determining the pillar width parameter based on the minimum quantity of the fixed device available memory and a minimum quantity of the mobile device available memory.

The method continues at step354where the processing module determines a LAN pillar width value based on the decode threshold parameter, the pillar width parameter, and the quantities of the LAN available memories, wherein the LAN pillar width value is equal to or greater than a value of the decode threshold parameter. Alternatively, the processing module determines the LAN pillar width value to be less than a value of the pillar width parameter. The method continues at step356where the processing module determines a WAN pillar width value based on the decode threshold parameter and the pillar width parameter, wherein the WAN pillar width value is equal to or greater than the value of the decode threshold parameter, wherein, for data that is encoded into a set of encoded data slices in accordance with the dispersed storage error coding function, the decode threshold parameter, and the pillar width parameter, a LAN pillar width value of encoded data slices of the set of encoded data slices are selected for storage in the LAN available memories, and a WAN pillar width value of encoded data slices of the set of encode data slices for storage in a distributed storage network (DSN) memory of the WAN. Alternatively, the processing module determines the WAN pillar width value to be less than the value of the pillar width parameter.

FIG. 11is a flowchart illustrating an example of transferring data. The method begins with step360where a processing module determines whether to transfer encoded data slices stored in a local Flash memory when detecting a shutdown. The detecting a shutdown includes or more of receiving a shutdown message, detecting a power failure, detecting a processing failure, executing a query, receiving a message, receiving a command, receiving a request, looking up a predetermination, and looking up a schedule. The determination may be based on one or more of a storage requirement, a storage indicator, a memory type indicator, a slice priority indicator, a data type indicator, a user identifier (ID), a vault ID, a slice volume indicator, an estimated time to transfer slices, and an estimated time to power off. For example, the processing module determines to transfer the encoded data slices when a slice priority indicator associated with the encoded data slices compares favorably to a slice priority threshold, and the estimated time to transfer slices compares favorably to the estimated time to power off. The method loops at step360when the processing module determines not to transfer the encoded data slices. The method continues to step362when the processing module determines to transfer the encoded data slices.

The method continues at step362where the processing module determines a group of encoded data slices stored in the local flash memory to transfer. The group of encoded data slices may include at least a decode threshold number of encoded data slices per set of encoded data slices. The determination may be based on one or more of error coding dispersal storage function parameters, the storage requirement, the storage indicator, the memory type indicator, the slice priority indicator, the data type indicator, the user ID, the vault ID, the slice volume indicator, the estimated time to transfer slices, and the estimated time to power off. For example, the processing module determines the group of encoded data slices to include 12 encoded data slices per set of encoded data slices when the error coding dispersal storage option parameters includes a read threshold of 12 and a decode threshold of 10.

The method continues at step364where the processing module determines where to store the group of encoded data slices to produce at least one storage location. The storage location may include one or more other user devices, wherein the one or more other user devices are affiliated with a current user device such that each of the other user devices is associated with a storage indicator indicating a favorable level of Flash memory capacity sufficient to store the group of encoded data slices. The determination may be based on one or more of an alternative memory list, a query, a message, a size of the group of encoded data slices, a predetermination, a lookup, a request, a command, and a message.

The method continues at step368where the processing module transfers the group of encoded data slices to the at least one storage location. The transferring may include retrieving the group of encoded data slices and outputting the group of encoded data slices to the lease one storage location. The method continues at step370where the process module outputs a message indicating that the group of encoded data slices has been transferred. The outputting may include sending the message to one or more of another user device, a dispersed storage (DS) processing unit, and a DS managing unit. The processing module may receive a subsequent shutdown message in response to sending the message. Next, the processing module completes a final shutdown process when receiving a shutdown message.

FIG. 12Ais a flowchart illustrating an example of generating an encoded data slice storage solicitation message. The method begins with step372where a processing module determines a utilization level of a local flash memory. The method continues at step374where the processing module determines whether the utilization level compares favorably to a utilization threshold. For example, the processing module determines that the utilization level compares favorably to the utilization threshold when the utilization level is less than the utilization threshold. The method branches to step376when the processing module determines that the utilization level compares favorably to the utilization threshold. The method loops back to step372when the processing module determines that the utilization level does not compare favorably to the utilization threshold (e.g., no storage capacity to share).

The method continues at step376where the processing module generates and sends an encoded data slice storage solicitation message to one or more other user devices. The solicitation message includes one or more of an available amount of memory indicator, a user device identifier (ID), a performance history indicator, a group ID, a vault ID, and a one-time/on-going indicator (e.g., one-time: transfer now only; on-going: transfer now and for subsequent transfer and storage operations). The sending includes outputting the data slice storage slice solicitation message to one or more of a random user device, an affiliated user device, a group of affiliated user devices, one or more other user devices that previously output a request for stories message, and a list of targets. The method continues step378where the processing module receives a plurality of encoded data slices from the one or more other user devices. The method continues at step380where the processing module stores the plurality of encoded data slices in the local flash memory. The method may repeat back to step372.

FIG. 12Bis a flowchart illustrating an example of processing an encoded data slice storage solicitation message that includes similar steps toFIG. 11. The method begins at step382where a processing module receives an encoded data slice storage solicitation message from another user device. The method continues at step384where the processing module determines whether to transfer encoded data slices that are stored in a local Flash memory. The determination may be based on one or more of the storage requirement, a storage indicator, a utilization level indicator, a utilization level threshold, a permissions list, an affiliation list, information in the solicitation message, a predetermination, a lookup, a message, a request, and a command. For example, the processing module determines to transfer encoded data slices when a user identifier (ID) associated with the solicitation message compares favorably to the permissions list and the utilization level indicator compares unfavorably to the utilization level threshold. The method loops back to step382when the processing module determines not to transfer encoded data slices. The method continues to step362ofFIG. 11when the processing module determines to transfer encoded data slices.

The method continues with step362ofFIG. 11where the processing module determines a group of encoded data slices stored in the local Flash memory to transfer. The method continues at step388where the processing module transfers the group of encoded data slices to the other user device. The transferring includes retrieving the group of encoded data slices from the local flash memory and outputting the group of encoded data slices to the other user device.

The term “module” is used in the description of the various embodiments of the present invention. A module includes a processing module, a functional block, hardware, and/or software stored on memory for performing one or more functions as may be described herein. Note that, if the module is implemented via hardware, the hardware may operate independently and/or in conjunction software and/or firmware. As used herein, a module may contain one or more sub-modules, each of which may be one or more modules.