Patent Publication Number: US-10761917-B2

Title: Using global namespace addressing in a dispersed storage network

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims priority pursuant to 35 U.S.C. § 120 as a continuation-in-part of U.S. Utility application Ser. No. 16/029,898, entitled “MONITORING OF STORAGE UNITS IN A DISPERSED STORAGE NETWORK,” filed Jul. 9, 2018, which claims priority pursuant to 35 U.S.C. § 120 as a continuation-in-part of U.S. Utility application Ser. No. 14/613,899, entitled “GENERATING MOLECULAR ENCODING INFORMATION FOR DATA STORAGE,” filed Feb. 4, 2015, issued as U.S. Pat. No. 10,020,826 on Jul. 10, 2018, which claims priority pursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No. 61/974,110, entitled “accessing data in a dispersed storage network,” filed Apr. 2, 2014, all of which are hereby incorporated herein by reference in their entirety and made part of the present U.S. Utility Patent Application for all purposes. 
    
    
     STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
     Not applicable. 
     INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC 
     Not applicable. 
     BACKGROUND OF THE INVENTION 
     Technical Field of the Invention 
     This invention relates generally to computer networks and more particularly to dispersing error encoded data. 
     Description of Related Art 
     Computing devices are known to communicate data, process data, and/or store data. Such computing devices range from wireless smart phones, laptops, tablets, personal computers (PC), work stations, and video game devices, to data centers that support millions of web searches, stock trades, or on-line purchases every day. In general, a computing device includes a central processing unit (CPU), a memory system, user input/output interfaces, peripheral device interfaces, and an interconnecting bus structure. 
     As is further known, a computer may effectively extend its CPU by using “cloud computing” to perform one or more computing functions (e.g., a service, an application, an algorithm, an arithmetic logic function, etc.) on behalf of the computer. Further, for large services, applications, and/or functions, cloud computing may be performed by multiple cloud computing resources in a distributed manner to improve the response time for completion of the service, application, and/or function. For example, Hadoop is an open source software framework that supports distributed applications enabling application execution by thousands of computers. 
     In addition to cloud computing, a computer may use “cloud storage” as part of its memory system. As is known, cloud storage enables a user, via its computer, to store files, applications, etc. on an Internet storage system. The Internet storage system may include a RAID (redundant array of independent disks) system and/or a dispersed storage system that uses an error correction scheme to encode data for storage. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S) 
         FIG. 1  is a schematic block diagram of an embodiment of a dispersed or distributed storage network (DSN) in accordance with the present invention; 
         FIG. 2  is a schematic block diagram of an embodiment of a computing core in accordance with the present invention; 
         FIG. 3  is a schematic block diagram of an example of dispersed storage error encoding of data in accordance with the present invention; 
         FIG. 4  is a schematic block diagram of a generic example of an error encoding function in accordance with the present invention; 
         FIG. 5  is a schematic block diagram of a specific example of an error encoding function in accordance with the present invention; 
         FIG. 6  is a schematic block diagram of an example of a slice name of an encoded data slice (EDS) in accordance with the present invention; 
         FIG. 7  is a schematic block diagram of an example of dispersed storage error decoding of data in accordance with the present invention; 
         FIG. 8  is a schematic block diagram of a generic example of an error decoding function in accordance with the present invention; 
         FIG. 9A  is a schematic block diagram of an embodiment of a dispersed storage network (DSN) in accordance with the present disclosure; 
         FIG. 9B  is a flowchart illustrating an example of accessing data in accordance with the present disclosure; 
         FIG. 10A  is a schematic block diagram of another embodiment of a dispersed storage network (DSN) in accordance with the present disclosure; 
         FIG. 10B  is a flowchart illustrating another example of accessing data in accordance with the present disclosure; 
         FIG. 11A  is a schematic block diagram of another embodiment of a dispersed storage network (DSN) in accordance with the present disclosure; and 
         FIG. 11B  is a flowchart illustrating an example of monitoring storage units in accordance with the present disclosure. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       FIG. 1  is a schematic block diagram of an embodiment of a dispersed, or distributed, storage network (DSN)  10  that includes a plurality of computing devices  12 - 16 , a managing unit  18 , an integrity processing unit  20 , and a DSN memory  22 . The components of the DSN  10  are coupled to a network  24 , which may include one or more wireless and/or wire lined communication systems; one or more non-public intranet systems and/or public interne systems; and/or one or more local area networks (LAN) and/or wide area networks (WAN). 
     The DSN memory  22  includes a plurality of storage units  36  that may be located at geographically different sites (e.g., one in Chicago, one in Milwaukee, etc.), at a common site, or a combination thereof. For example, if the DSN memory  22  includes eight storage units  36 , each storage unit is located at a different site. As another example, if the DSN memory  22  includes eight storage units  36 , all eight storage units are located at the same site. As yet another example, if the DSN memory  22  includes eight storage units  36 , a first pair of storage units are at a first common site, a second pair of storage units are at a second common site, a third pair of storage units are at a third common site, and a fourth pair of storage units are at a fourth common site. Note that a DSN memory  22  may include more or less than eight storage units  36 . Further note that each storage unit  36  includes a computing core (as shown in  FIG. 2 , or components thereof) and a plurality of memory devices for storing dispersed error encoded data. 
     Each of the computing devices  12 - 16 , the managing unit  18 , and the integrity processing unit  20  include a computing core  26 , which includes network interfaces  30 - 33 . Computing devices  12 - 16  may each be a portable computing device and/or a fixed computing device. A portable computing device may be a social networking device, a gaming device, a cell phone, a smart phone, a digital assistant, a digital music player, a digital video player, a laptop computer, a handheld computer, a tablet, a video game controller, and/or any other portable device that includes a computing core. A fixed computing device may be a computer (PC), 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. Note that each of the managing unit  18  and the integrity processing unit  20  may be separate computing devices, may be a common computing device, and/or may be integrated into one or more of the computing devices  12 - 16  and/or into one or more of the storage units  36 . 
     Each interface  30 ,  32 , and  33  includes software and hardware to support one or more communication links via the network  24  indirectly and/or directly. For example, interface  30  supports a communication link (e.g., wired, wireless, direct, via a LAN, via the network  24 , etc.) between computing devices  14  and  16 . As another example, interface  32  supports communication links (e.g., a wired connection, a wireless connection, a LAN connection, and/or any other type of connection to/from the network  24 ) between computing devices  12  and  16  and the DSN memory  22 . As yet another example, interface  33  supports a communication link for each of the managing unit  18  and the integrity processing unit  20  to the network  24 . 
     Computing devices  12  and  16  include a dispersed storage (DS) client module  34 , which enables the computing device to dispersed storage error encode and decode data (e.g., data  40 ) as subsequently described with reference to one or more of  FIGS. 3-8 . In this example embodiment, computing device  16  functions as a dispersed storage processing agent for computing device  14 . In this role, computing device  16  dispersed storage error encodes and decodes data on behalf of computing device  14 . With the use of dispersed storage error encoding and decoding, the DSN  10  is tolerant of a significant number of storage unit failures (the number of failures is based on parameters of the dispersed storage error encoding function) without loss of data and without the need for a redundant or backup copies of the data. Further, the DSN  10  stores data for an indefinite period of time without data loss and in a secure manner (e.g., the system is very resistant to unauthorized attempts at accessing the data). 
     In operation, the managing unit  18  performs DS management services. For example, the managing unit  18  establishes distributed data storage parameters (e.g., vault creation, distributed storage parameters, security parameters, billing information, user profile information, etc.) for computing devices  12 - 14  individually or as part of a group of user devices. As a specific example, the managing unit  18  coordinates creation of a vault (e.g., a virtual memory block associated with a portion of an overall namespace of the DSN) within the DSN memory  22  for a user device, a group of devices, or for public access and establishes per vault dispersed storage (DS) error encoding parameters for a vault. The managing unit  18  facilitates storage of DS error encoding parameters for each vault by updating registry information of the DSN  10 , where the registry information may be stored in the DSN memory  22 , a computing device  12 - 16 , the managing unit  18 , and/or the integrity processing unit  20 . 
     The managing unit  18  creates and stores user profile information (e.g., an access control list (ACL)) in local memory and/or within memory of the DSN memory  22 . The user profile information includes authentication information, permissions, and/or the security parameters. The security parameters may include encryption/decryption scheme, one or more encryption keys, key generation scheme, and/or data encoding/decoding scheme. 
     The managing unit  18  creates billing information for a particular user, a user group, a vault access, public vault access, etc. For instance, the managing unit  18  tracks the number of times a user accesses a non-public vault and/or public vaults, which can be used to generate a per-access billing information. In another instance, the managing unit  18  tracks the amount of data stored and/or retrieved by a user device and/or a user group, which can be used to generate a per-data-amount billing information. 
     As another example, the managing unit  18  performs network operations, network administration, and/or network maintenance. Network operations includes authenticating user data allocation requests (e.g., read and/or write requests), managing creation of vaults, establishing authentication credentials for user devices, adding/deleting components (e.g., user devices, storage units, and/or computing devices with a DS client module  34 ) to/from the DSN  10 , and/or establishing authentication credentials for the storage units  36 . Network administration includes monitoring devices and/or units for failures, maintaining vault information, determining device and/or unit activation status, determining device and/or unit loading, and/or determining any other system level operation that affects the performance level of the DSN  10 . Network maintenance includes facilitating replacing, upgrading, repairing, and/or expanding a device and/or unit of the DSN  10 . 
     The integrity processing unit  20  performs rebuilding of ‘bad’ or missing encoded data slices. At a high level, the integrity processing unit  20  performs rebuilding by periodically attempting to retrieve/list encoded data slices, and/or slice names of the encoded data slices, from the DSN memory  22 . For retrieved encoded slices, they are checked for errors due to data corruption, outdated version, etc. If a slice includes an error, it is flagged as a ‘bad’ slice. For encoded data slices that were not received and/or not listed, they are flagged as missing slices. Bad and/or missing slices are subsequently rebuilt using other retrieved encoded data slices that are deemed to be good slices to produce rebuilt slices. The rebuilt slices are stored in the DSN memory  22 . 
       FIG. 2  is a schematic block diagram of an embodiment of a computing core  26  that includes a processing module  50 , a memory controller  52 , main memory  54 , a video graphics processing unit  55 , an input/output (IO) controller  56 , a peripheral component interconnect (PCI) interface  58 , an IO interface module  60 , at least one IO device interface module  62 , a read only memory (ROM) basic input output system (BIOS)  64 , and one or more memory interface modules. The one or more memory interface module(s) includes one or more of a universal serial bus (USB) interface module  66 , a host bus adapter (HBA) interface module  68 , a network interface module  70 , a flash interface module  72 , a hard drive interface module  74 , and a DSN interface module  76 . 
     The DSN interface module  76  functions to mimic a conventional operating system (OS) file system interface (e.g., network file system (NFS), flash file system (FFS), disk file system (DFS), file transfer protocol (FTP), web-based distributed authoring and versioning (WebDAV), etc.) and/or a block memory interface (e.g., small computer system interface (SCSI), internet small computer system interface (iSCSI), etc.). The DSN interface module  76  and/or the network interface module  70  may function as one or more of the interface  30 - 33  of  FIG. 1 . Note that the IO device interface module  62  and/or the memory interface modules  66 - 76  may be collectively or individually referred to as IO ports. 
       FIG. 3  is a schematic block diagram of an example of dispersed storage error encoding of data. When a computing device  12  or  16  has data to store it disperse storage error encodes the data in accordance with a dispersed storage error encoding process based on dispersed storage error encoding parameters. The dispersed storage error encoding parameters include an encoding function (e.g., information dispersal algorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding, non-systematic encoding, on-line codes, etc.), a data segmenting protocol (e.g., data segment size, fixed, variable, etc.), and per data segment encoding values. The per data segment encoding values include a total, or pillar width, number (T) of encoded data slices per encoding of a data segment (i.e., in a set of encoded data slices); a decode threshold number (D) of encoded data slices of a set of encoded data slices that are needed to recover the data segment; a read threshold number (R) of encoded data slices to indicate a number of encoded data slices per set to be read from storage for decoding of the data segment; and/or a write threshold number (W) to indicate a number of encoded data slices per set that must be accurately stored before the encoded data segment is deemed to have been properly stored. The dispersed storage error encoding parameters may further include slicing information (e.g., the number of encoded data slices that will be created for each data segment) and/or slice security information (e.g., per encoded data slice encryption, compression, integrity checksum, etc.). 
     In the present example, Cauchy Reed-Solomon has been selected as the encoding function (a generic example is shown in  FIG. 4  and a specific example is shown in  FIG. 5 ); the data segmenting protocol is to divide the data object into fixed sized data segments; and the per data segment encoding values include: a pillar width of 5, a decode threshold of 3, a read threshold of 4, and a write threshold of 4. In accordance with the data segmenting protocol, the computing device  12  or  16  divides the data (e.g., a file (e.g., text, video, audio, etc.), a data object, or other data arrangement) into a plurality of fixed sized data segments (e.g., 1 through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more). The number of data segments created is dependent of the size of the data and the data segmenting protocol. 
     The computing device  12  or  16  then disperse storage error encodes a data segment using the selected encoding function (e.g., Cauchy Reed-Solomon) to produce a set of encoded data slices.  FIG. 4  illustrates a generic Cauchy Reed-Solomon encoding function, which includes an encoding matrix (EM), a data matrix (DM), and a coded matrix (CM). The size of the encoding matrix (EM) is dependent on the pillar width number (T) and the decode threshold number (D) of selected per data segment encoding values. To produce the data matrix (DM), the data segment is divided into a plurality of data blocks and the data blocks are arranged into D number of rows with Z data blocks per row. Note that Z is a function of the number of data blocks created from the data segment and the decode threshold number (D). The coded matrix is produced by matrix multiplying the data matrix by the encoding matrix. 
       FIG. 5  illustrates a specific example of Cauchy Reed-Solomon encoding with a pillar number (T) of five and decode threshold number of three. In this example, a first data segment is divided into twelve data blocks (D1-D12). The coded matrix includes five rows of coded data blocks, where the first row of X11-X14 corresponds to a first encoded data slice (EDS 1_1), the second row of X21-X24 corresponds to a second encoded data slice (EDS 2_1), the third row of X31-X34 corresponds to a third encoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to a fourth encoded data slice (EDS 4_1), and the fifth row of X51-X54 corresponds to a fifth encoded data slice (EDS 5_1). Note that the second number of the EDS designation corresponds to the data segment number. 
     Returning to the discussion of  FIG. 3 , the computing device also creates a slice name (SN) for each encoded data slice (EDS) in the set of encoded data slices. A typical format for a slice name  80  is shown in  FIG. 6 . As shown, the slice name (SN)  80  includes a pillar number of the encoded data slice (e.g., one of 1-T), a data segment number (e.g., one of 1-Y), a vault identifier (ID), a data object identifier (ID), and may further include revision level information of the encoded data slices. The slice name functions as, at least part of, a DSN address for the encoded data slice for storage and retrieval from the DSN memory  22 . 
     As a result of encoding, the computing device  12  or  16  produces a plurality of sets of encoded data slices, which are provided with their respective slice names to the storage units for storage. As shown, the first set of encoded data slices includes EDS 1_1 through EDS 5_1 and the first set of slice names includes SN 1_1 through SN 5_1 and the last set of encoded data slices includes EDS 1_Y through EDS 5_Y and the last set of slice names includes SN 1_Y through SN 5_Y. 
       FIG. 7  is a schematic block diagram of an example of dispersed storage error decoding of a data object that was dispersed storage error encoded and stored in the example of  FIG. 4 . In this example, the computing device  12  or  16  retrieves from the storage units at least the decode threshold number of encoded data slices per data segment. As a specific example, the computing device retrieves a read threshold number of encoded data slices. 
     To recover a data segment from a decode threshold number of encoded data slices, the computing device uses a decoding function as shown in  FIG. 8 . As shown, the decoding function is essentially an inverse of the encoding function of  FIG. 4 . The coded matrix includes a decode threshold number of rows (e.g., three in this example) and the decoding matrix in an inversion of the encoding matrix that includes the corresponding rows of the coded matrix. For example, if the coded matrix includes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2, and 4, and then inverted to produce the decoding matrix. 
       FIG. 9A  is a schematic block diagram of an embodiment of a dispersed storage network (DSN) that includes at least two user devices  1 - 2 , a plurality of distributed storage (DS) processing units  1 -D, and the distributed storage network module  22  of  FIG. 1 . The DSN may further include the network  24  of  FIG. 1 . The user devices  1 - 2  may be implemented utilizing the computing device  12  of  FIG. 1 . The storage units  1 -D may be implemented utilizing the storage unit  16  of  FIG. 1 . 
     The DSN functions to store data as stored data and to retrieve the stored data to reproduce the data. In an example of operation of storing the data, the user device  1  selects a storage unit of the storage units  1 -D based on an identifier of a data object for storage. The selecting may be based on one or more of an address space mapping and performing a deterministic function on the identifier of the data object. For example, the user device  1  selects the storage unit  2  when the identifier of the data object indicates data object  2 - 1  and the address mapping indicates that the data object  2 - 1  is affiliated with storage unit  2 . As another example, the user device  1  selects the storage unit  2  when a result of applying the deterministic function to an identifier of another data object  1 - 1  produces an indicator that includes an identifier of the storage unit  1 . 
     Having selected the storage unit  2 , the user device  1  issues a data access message  2  to the storage unit  2 , where the data access message  2  includes a store data request. The store data request includes the data object  2 - 1 . Having received the data object  2 - 1 , the storage unit  2  caches the data object  2 - 1  in a local memory of the storage unit  2  in accordance with the address space mapping and an available capacity level. For example, the storage unit  2  caches the data object  2 - 1  when the available capacity level compares favorably (e.g., greater than) to a minimum available capacity threshold level and the address space mapping indicates that the data object  2 - 1  is affiliated with the storage unit  2 . 
     The storage unit  2  dispersed storage error encodes the data object  2 - 1  to produce a plurality of sets of encoded data slices. Having produced the plurality of sets of encoded data slices, the storage unit  2  issues a DSN message to the DSN module  22  to facilitate storage of the plurality of sets of encoded data slices in the DSN module  22 . For example, the storage unit  2  generates a set of write slice requests that includes the plurality of sets of encoded data slices and sends the set of write slice requests to the DSN module  22  as the DSN message  2 . 
     When the available capacity level of the storage unit  2  does not compare favorably to the minimum available capacity threshold level, the storage unit  2  selects at least one locally stored data object for transfer. For example, the storage unit  2  selects a data object  1 -N associated with an address at an end of an address range associated with the storage unit  2 . Having selected the store data object for transfer, the storage unit  2  issues a transfer message  2 - 1  to the storage unit  1  that includes the data object  1 -N. One or more of the storage unit  1  and storage unit  2  facilitates updating of the address space mapping to indicate that the data object  1 -N is affiliated with storage unit  1  and is no longer affiliated with storage unit  2 . Having updated the address space mapping, the one or more of the storage units  1 - 2  sends the address space mapping that has been updated to one or more entities of the DSN (e.g., to the DSN managing unit  18  of  FIG. 1  for further distribution, to other storage units, to the user devices  1 - 2 ). 
     In an example of operation to retrieve the stored data to reproduce the data, the user device  2  identifies the storage unit  2  as affiliated with the data object  2 - 1  for retrieval based on accessing the address space mapping. Having identified the storage unit  2 , the user device  2  issues a data access message  2  to the identified storage unit  2 . For example, the user device  2  issues a retrieve data request to the storage unit  2 , where the retrieve data request includes the identifier of the data object  2 - 1 . 
     Having received the retrieve data request from the user device  2 , the storage unit  2  obtains the data object  2 - 1 . The obtaining includes at least one of retrieving the data object  2 - 1  from the local memory of storage unit  2  and recovering the data object  2 - 1  from the DSN module  22 . When the data object  2 - 1  is available from the local memory of the storage unit  2 , the storage unit  2  issues a data access message  2  to the user device  2 , where the data access message includes the data object  2 - 1 . For example, the storage unit  2  sends a retrieve data response to the user device  2 , where the retrieve data response includes the data object  2 - 1 . 
     When the data object  2 - 1  is not available from the local memory of the storage unit  2 , the storage unit  2  issues a DSN message  2  to the DSN module  22 . For example, the storage unit  2  issues a read threshold number of read slice requests to the DSN module  22  with regards to the data object  2 - 1 , receives read slice responses, and decodes encoded data slices of the received read slice responses to reproduce the data object  2 - 1 . 
       FIG. 9B  is a flowchart illustrating an example of accessing data. The accessing includes one or more of storing the data, transferring the data, and retrieving the data. The method begins or continues, when storing a data object, at step  360  where a requesting entity (e.g., a user device) identifies an access module (e.g., a distributed storage (DS) processing unit) for a dispersed storage network (DSN) based on an identifier of the data object for storage. For example, the requesting entity accesses an address-based mapping utilizing an identifier of the data object to retrieve an identifier of the access module that is associated with the identifier the data object. 
     The method continues at step  362  where the requesting entity sends the data object to the access module for storage in the DSN. The method continues at step  364  where the access module stores the data object in the DSN. For example, the access module dispersed storage error encodes the data to produce a plurality of sets of encoded data slices and sends the plurality of sets of encoded data slices to a set of storage units for storage. The method continues at step  366  where the access module facilitates storage of the data object in a cache memory in accordance with the address-based mapping. For example, the access module stores the received data object in a memory of the identified access module. As another example, the access module sends the data object to another access module for storage, where the other access module is affiliated with the identifier of the data object. 
     When transferring the data object, the method continues at step  368  where the access module determines whether to transfer one or more data objects from the cache memory. The determining may be based on one or more of an available cache memory storage level, a frequency of access level for the one or more data objects, the available input/output resources, and an elapsed time of storage of the one or more data objects. For example, the access module determines to transfer a first data object from the cache memory when the first data object is associated with a frequency of access level that compares unfavorably (e.g., greater than) to a maximum frequency of access threshold level. 
     When transferring the data object, the method continues at step  370  where the access module identifies a cached data object for transfer and another access module. For example, the access module selects a cached data object associated with an identifier at an end of an address range associated with the access module where the identifier at the end meets a beginning identifier of another address range associated with another access module. Having selected the cached data object, the access module initiates a capacity query to the other access module and receives a favorable query response (e.g., to approve transfer of the identified cached data object). 
     The method continues at step  372  where the access module facilitates transfer of the cached data object to the other access module. For example, the access module issues a transfer message to the other access module, where the transfer message includes the identified cached data object and an identifier of the cached data object. Having received the transfer message, the other access module stores the data object in a local cache memory associated with the other access module. Having stored the data object in the local cache memory, the other access module may verify that the data object is available for retrieval from the DSN. Having stored the data object in the local cache memory associated with the other access module, the other access module sends a transfer confirmation message to the access module indicating that the data object has been successfully transferred. Having received the transfer confirmation message, the method continues at step  374  where the access module facilitates updating the address based mapping to disassociate the data object with the access module and associate the data object with the other access module. 
     When retrieving the data object from the DSN, the method continues at  376  where the requesting entity identifies the other access module based on the identifier of the data object for retrieval. For example, the other access module recovers an identifier of the other access module from the address space mapping using the identifier of the data object. The method continues at step  378  where the requesting entity issues a data object retrieval request to the other access module. The issuing includes generating the data object retrieval request to include the identifier of the data object and sending the data object retrieval request to the other access module. 
     The method continues at step  380  where the other access module retrieves the data object from the local cache memory of the other access module when the data object is available from the cache memory of the other access module. Alternatively, the other access module retrieves the data object from the DSN when the data object is unavailable from the local cache memory of the other access module. The method continues at step  382  where the other access module sends the data object to the requesting entity. 
       FIG. 10A  is a schematic block diagram of another embodiment of a dispersed storage network (DSN) that includes a content source  400 , an ingestion distributed storage (DS) processing unit  402 , the DSN module  22  of  FIG. 1 , a retrieval storage unit  403 , and the computing device  12  of  FIG. 1 . Alternatively, the DSN further includes the network  24  of  FIG. 1 . The ingestion storage unit  402  and the retrieval storage unit  403  may be implemented utilizing the storage unit  16  of  FIG. 1 . The ingestion storage unit  402  includes a content ingestion module  404  and the DS client module  34  of  FIG. 1 . The retrieval storage unit  403  includes a content retrieval module  406  and the DS client module  34  of  FIG. 1 . The content source  400 , the content ingestion module  404 , and the content retrieval module  406  may be implemented utilizing one or more of the processing module  88  of  FIG. 3 , the storage unit  16  of  FIG. 1 , the computing device  12 , a server, a computing device, and the DS client module  34 . 
     The system functions to ingest content for storage as stored content in the DSN module  22  and to retrieve the stored content. The content includes one or more of files and streams. The files and streams include one or more content types. The content types include one or more of multimedia, audio, text, messages, movies, movie trailers, web videos, music recordings, etc. In an example of operation of the ingesting of the content for storage, the content ingestion module  404  receives the content  408  from the content source  400 . The content  408  may include one or more formats of common source material. Formats include one or more of encoding algorithms and encoding parameters associated with representing the source material in a digital form. 
     Having received the content  408 , the content ingestion module  404  transforms the content  408  into one or more formats  1 -F in accordance with a formatting scheme. The formatting scheme includes one or more of a number of formats, a type of format for each of the formats, and parameters associated with each format. For example, a first format includes a 2 Mbps standard definition video stream and a second format includes a 50 Mbps high-definition video stream. 
     For each of the formats  1 -F, the DS client module  34  of the ingestion storage unit  402  dispersed storage error encodes the format to produce a plurality of sets of encoded data slices. Having generated the plurality of sets of encoded data slices, the DS client module  34  generates a plurality of sets of slice names for the plurality of sets of encoded data slices based on one or more of a content type indicator and a content identifier. Having generated the plurality of sets of slice names, the DS client module  34  facilitates storage of the plurality of sets of encoded data slices. For example, the DS client module  34  generates a set of write slice requests and sends the set of write slice requests to the DSN module  22 , where the set of write slice requests includes the plurality of sets of encoded data slices and the plurality of sets of slice names. For instance, the DS client module  34  issues write slice requests  3  for a third format from the content ingestion module  400  for, where the write slice requests  3  includes a set of write slice requests. 
     Having facilitated the storage of the plurality of sets of encoded data slices for each format, the DS client module  34  of the ingestion storage unit  402  facilitates updating one or more of a dispersed hierarchical index and a DSN directory to associate identifiers of each of the formats and logical DSN addresses of the storage of each of the plurality of sets of encoded data slices. For example, the DS client module  34  updates the dispersed hierarchical index to include a format 3 identifier with a source name associated with the plurality of sets of slice names corresponding to the plurality of sets of encoded data slices from encoding of the format 3. 
     In an example of operation of retrieving stored content, the computing device  12  issues a content request  410  to the retrieval storage unit  403 , where the content request  410  includes one or more of a content identifier, a time indicator, and a type indicator of one or more desired formats associated with content of the content identifier. Having received the content request  410 , the content retrieval module  406  accesses one or more of the dispersed hierarchical index and the DSN directory using one or more of a content ID, the time indicator, and the type indicators of the one or more desired formats to identify a logical DSN address for each desired format. 
     Having identified the DSN addresses for each of the desired formats, the DS client module  34  of the retrieval storage unit  403  recovers at least some of the plurality of sets of encoded data slices using the DSN addresses. For example, the DS client module  34  issues a set of read slice requests to the DSN module  22  and receives read slice responses  412 . The set of read slice requests includes a plurality of sets of slice names associated with each of the plurality sets of encoded data slices of each of the desired formats. 
     Having received the read slice responses  412 , the DS client module  34  of the retrieval storage unit  403  dispersed storage error decodes a decode threshold number of encoded data slices for each set of the plurality of sets of encoded data slices of each plurality of sets of encoded data slices to reproduce the one or more formats  414 . Having recovered the one or more formats  414 , the content retrieval module  406  sends requested content  416  to the computing device  12 , where the requested content  416  includes the reproduced one or more formats  414 . 
       FIG. 10B  is a flowchart illustrating another example of accessing data. The method begins or continues, when ingesting data, at step  420  where an ingestion unit (e.g., a distributed storage (DS) processing unit utilized for ingestion) receives content for storage in a set of storage units. The ingestion unit may further receive one or more of an identifier of the content, a content size indicator, a content format indicator, and a content type indicator. The method continues at step  422  where the ingestion unit transforms the content into one or more formats. For example, the ingestion unit re-encodes the content into a plurality of other formats in accordance with a formatting scheme. 
     For each format, the method continues at step  424  where the ingestion unit dispersed storage error encodes the format to produce a plurality of sets of encoded data slices. For each format, the method continues at step  426  where the ingestion unit generates a logical address. For example, the ingestion unit produces a unique source name for each format based on one or more of the content identifier, a content type, and a format identifier. 
     For each logical address, the method continues at step  428  where the ingestion unit generates a plurality of sets of slice names. For example, the ingestion unit generates each slice name to include an associated unique source name. For each format, the method continues at step  430  where the ingestion unit facilitates storage of the corresponding plurality of sets of encoded data slices in the set of storage units using a corresponding plurality of sets of slice names. For example, the ingestion unit generates a set of write slice requests and sends the set of write slice requests to the set of storage units, where the set of write slice requests includes the corresponding plurality of sets of encoded data slices and the corresponding plurality of sets of slice names. 
     For each format, the method continues at step  432  where the ingestion unit updates one or more of a directory and a dispersed hierarchical index to associate one or more of a content identifier, the format, and the associated logical address. For example, the ingestion unit adds index keys to entries of the dispersed hierarchical index, where the index keys are associated with identifiers of the formats and the entries includes the logical address of the formats. 
     The method continues or begins, when retrieving the data, at step  434  where a retrieval unit receives a content request, where the content request includes one or more of type indicators of one or more desired formats, the content ID, and a time identifier. The method continues at step  436  where the retrieval unit accesses one or more of the directory and the dispersed hierarchical index using the type indicators and the content ID to recover an associated logical address for each desired format. For example, the retrieval unit utilizes a type indicator as an index key to access the dispersed hierarchical index to recover a corresponding logical address for the desired format. 
     For each desired format, the method continues at step  438  where the retrieval unit recovers at least some sets of the plurality of sets of encoded data slices associated with the desired format from the set of storage units. For example, the retrieval unit converts the associated logical address into sets of slice names, issues a set of read slice requests that includes the sets of slice names, and receives at least a decode threshold number of encoded data slices for each set of encoded data slices. 
     For each desired format, the method continues at step  440  where the retrieval unit decodes the received at least some sets of the plurality of sets of encoded data slices to reproduce the content in the desired format. Alternatively, or in addition to, the retrieval unit restricts decoding of slices to encoded data slices associated with a desired time frame within a video stream in accordance with the time identifier. For each desired format, the method continues at step  442  where the retrieval unit outputs the reproduced content of the desired format to a requesting entity. 
       FIG. 11A  is a schematic block diagram of another embodiment of a dispersed storage network (DSN) that includes M distributed storage (DS) execution unit sets  1 -M implemented at a plurality of N sites  1 -N, the network  24  of  FIG. 1 , and the distributed storage network (DSN) managing unit  18  of  FIG. 1 . Each DS execution unit set includes a set of n DS execution units (alternatively referred to herein as “storage units” or, in the singular, as a “storage unit”). Each DS execution unit may be implemented utilizing the DS execution unit  36  of  FIG. 1 . As a specific example of the implementation of the M DS execution unit sets  1 -M at the N sites  1 -N, site  1  includes a first DS execution unit from each DS execution unit set, site  2  includes a second DS execution unit from each DS execution unit set, etc. For instance, the site  1  includes DS execution units  1 - 1 - 1 ,  2 - 1 - 1 ,  3 - 1 - 1 , through M- 1 - 1  (set, site, unit). As described below, a scalable approach is provided for detecting and reporting certain failure conditions that a target storage unit may not be able to self-report (e.g., loss of network connectivity, power failure, or a disabling failure of a critical component). 
     The illustrated DSN functions to establish monitoring resources for monitoring of one or more of the DS execution units and to perform the monitoring of the one or more DS execution units in accordance with the establishing of the monitoring resources. In an example of operation to establish the monitoring resources, the DSN managing unit  18  obtains DSN configuration information. Alternatively, any other module, unit, or DSN entity of the DSN may perform such steps described for the DSN managing unit  18 . The obtaining includes at least one of performing a lookup, accessing at least a portion of registry information, receiving the configuration information, initiating a query, and receiving a query response. The DSN configuration information includes one or more of site location information, power source information, configuration information of the network  24 , a number of sites indicator, a number of DS execution unit sets indicator, a mapping of DS execution units to each DS execution unit set, a mapping of each DS execution unit to a site, a rebuilding capability level of a DS execution unit, a foster encoded data slice storage capability level of a DS execution unit, a DS execution unit storage capacity level, and a DS execution unit storage utilization level. 
     Having obtained the DSN configuration information, the DSN managing unit  18  selects a target DS execution unit to be monitored. The selecting may be based on one or more of identifying a next DS execution unit from a list of DS execution units to be monitored, detecting a new DS execution unit, determining that the DS execution unit is not being monitored, determining that a timeframe has elapsed since a last monitoring of the DS execution unit, interpreting an error message associated with the DS execution unit, and receiving a request. 
     Having selected the target DS execution unit, the DSN managing unit  18  determines a number of monitoring DS execution units to associate with the target DS execution unit. The determining may be based on one or more of a DSN activity level, an expected failure rate level, a monitoring table, and a predetermination. For example, the DSN managing unit selects the number of the monitoring DS execution units to be 1 when the DSN activity level is greater than a high threshold level. As another example, the DSN managing unit selects the number of the monitoring DS execution units to be 3 when the DSN activity level is within an expected threshold level of an average DSN activity level and the monitoring table entry indicates to utilize three monitoring units when the DSN activity level is within the expected threshold level of the average DSN activity level. 
     Having determined the number of monitoring DS execution units, the DSN managing unit  18  determines an estimated level of failure correlation between the target DS execution unit and at least some of the other DS execution units of the plurality of DS execution units based on the DSN configuration information. For example, the DSN managing unit  18  indicates a higher than average estimated level of failure correlation between the target DS execution unit and another DS execution unit when the DSN configuration information indicates that the target DS execution unit and the other DS execution unit are implemented at a common site. As another example, the DSN managing unit  18  indicates a lower than average estimated level of failure correlation between the target DS execution unit and the other DS execution unit when the DSN configuration information indicates that the target DS execution unit and the other DS execution unit are implemented at different sites and are part of different DS execution unit sets. 
     Having determined the number of monitoring DS execution units, the DSN managing unit  18  selects at least some of the other DS execution units based on the estimated level of failure correlation and the number of monitoring DS execution units. For example, the DSN managing unit  18  rank orders other DS execution units by corresponding estimated levels of failure correlation and selects the number that is associated with a least amount of failure correlation. For instance, the DSN managing unit  18  selects three DS execution units  1 -N-n,  3 - 1 - 1 , and M-N-n when the target DS execution unit is DS execution unit  2 - 2 - 2  and the three DS execution units are associated with the least amount of failure correlation with regards to DS execution unit  2 - 2 - 2 . 
     Having selected the monitoring DS execution units, the DSN managing unit  18  assigns the selected monitoring DS execution units for the target DS execution unit. For example, the DSN managing unit  18  issues unit status information to the three selected monitoring DS execution units, where the unit status information includes a monitoring assignment request to monitor DS execution unit  2 - 2 - 2 . The monitoring assignment request may include one or more of an identifier of the target DS execution unit, identifiers of the monitoring DS execution units, a frequency of reporting schedule, a threshold for reporting, and a type of monitoring indicator. The type of monitoring indicator indicates one or more types of monitoring including one or more of sending a periodic ping to the target storage unit, receiving a ping response, sending data to the target storage unit, receiving a response to the sending of the data, exchanging security information, obtaining performance information relating to the target storage unit, and initiating a test involving the target storage unit and analyzing responsive test results. 
     In an example of operation to perform the monitoring, at least some of the assigned monitoring DS execution units perform a monitoring function in accordance with the type of monitoring indicator to monitor the target DS execution unit and to produce unit status information  450  that includes monitoring results. Having produced unit status information  450 , the assigned monitoring DS execution unit sends the unit status information  450  to the DSN managing unit  18  in accordance with one or more of a frequency of reporting schedule and the threshold for reporting. For example, the DS execution unit  3 - 1 - 1  continually monitors DS execution unit  2 - 2 - 2  and produces the unit status information  450 . The DS execution unit  3 - 1 - 1  interprets the unit status information  450  and determines to send the unit status information  450  to the DSN managing unit  18  when a portion of the unit status information compares unfavorably to a desired threshold level. As another example, the DS execution unit  3 - 1 - 1  determines to send the unit status information  450  to the DSN managing unit  18  when interpreting of the frequency of reporting schedule indicates to send the unit status information  450 . The DS execution unit  3 - 1 - 1  sends the unit status information  450  to the DSN managing unit  18  when the DS execution unit  3 - 1 - 1  determines to send the unit status information  450 . 
       FIG. 11B  is a flowchart illustrating an example of monitoring storage units. The method begins or continues at step  452  where one or more processing modules (e.g., of a distributed storage network (DSN) managing unit) selects a target storage unit for monitoring, where a dispersed storage network (DSN) includes a plurality of storage units that includes the storage unit. The selecting may be based on one or more of interpreting a selection list, detecting that no monitoring units are associated with the target storage unit, detecting activation of a new storage unit, and receiving a request. 
     The method continues at step  454  where the processing module obtains configuration information for the DSN. For example, the processing module accesses a portion of a system registry. The method continues at step  456  where the processing module determines a number of monitoring storage units to monitor the target storage unit. For example, the processing module selects a higher than average number of monitoring storage units when a DSN activity level is lower than an average DSN activity level. As another example, the processing module selects a lower than average number of monitoring storage units when an estimated storage unit failure rate is lower than an average storage unit failure rate. 
     For each of at least some of other storage units of the plurality of storage units, the method continues at step  458  where the processing module determines an estimated failure correlation level with the target storage unit based on the configuration information for the DSN. The method continues at step  460  where the processing module selects monitoring storage units based on the associated estimated failure correlation levels and the determined number of monitoring storage units. For example, the processing module selects monitoring storage units associated with minimal estimated failure correlation levels. 
     The method continues at step  462  where the processing module assigns the monitoring storage units to monitor the target storage unit. For example, the processing module issues a monitoring assignment message to each of the monitoring storage units and to the target storage unit, where the monitoring assignment message indicates a monitoring relationship between the assigned monitoring storage units and the target storage unit. 
     The method continues at step  464  where each monitoring storage unit monitors the target storage unit. For example, the monitoring storage unit, from time to time, initiates a status check message to the target storage unit, receives a status check response from the target storage unit, indicates a potential failure when not receiving a favorable status check response within a response timeframe, gathers statistics, and reports failures and the statistics to one or more of a managing unit, the target storage unit, and at least one of other monitoring storage units. 
     It is noted that terminologies as may be used herein such as bit stream, stream, signal sequence, etc. (or their equivalents) have been used interchangeably to describe digital information whose content corresponds to any of a number of desired types (e.g., data, video, speech, text, graphics, audio, etc. any of which may generally be referred to as ‘data’). 
     As may be used herein, the terms “substantially” and “approximately” provides an industry-accepted tolerance for its corresponding term and/or relativity between items. For some industries, an industry-accepted tolerance is less than one percent and, for other industries, the industry-accepted tolerance is 10 percent or more. Other examples of industry-accepted tolerance range from less than one percent to fifty percent. Industry-accepted tolerances correspond to, but are not limited to, component values, integrated circuit process variations, temperature variations, rise and fall times, thermal noise, dimensions, signaling errors, dropped packets, temperatures, pressures, material compositions, and/or performance metrics. Within an industry, tolerance variances of accepted tolerances may be more or less than a percentage level (e.g., dimension tolerance of less than +/−1%). Some relativity between items may range from a difference of less than a percentage level to a few percent. Other relativity between items may range from a difference of a few percent to magnitude of differences. 
     As may also be used herein, the term(s) “configured to”, “operably coupled to”, “coupled to”, and/or “coupling” includes direct coupling between items and/or indirect coupling between items via an intervening item (e.g., an item includes, but is not limited to, a component, an element, a circuit, and/or a module) where, for an example of indirect coupling, the intervening item does not modify the information of a signal but may adjust its current level, voltage level, and/or power level. As may further be used herein, inferred coupling (i.e., where one element is coupled to another element by inference) includes direct and indirect coupling between two items in the same manner as “coupled to”. 
     As may even further be used herein, the term “configured to”, “operable to”, “coupled to”, or “operably coupled to” indicates that an item includes one or more of power connections, input(s), output(s), etc., to perform, when activated, one or more its corresponding functions and may further include inferred coupling to one or more other items. As may still further be used herein, the term “associated with”, includes direct and/or indirect coupling of separate items and/or one item being embedded within another item. 
     As may be used herein, the term “compares favorably”, indicates that a comparison between two or more items, signals, etc., provides a desired relationship. For example, when the desired relationship is that signal  1  has a greater magnitude than signal  2 , a favorable comparison may be achieved when the magnitude of signal  1  is greater than that of signal  2  or when the magnitude of signal  2  is less than that of signal  1 . As may be used herein, the term “compares unfavorably”, indicates that a comparison between two or more items, signals, etc., fails to provide the desired relationship. 
     As may be used herein, one or more claims may include, in a specific form of this generic form, the phrase “at least one of a, b, and c” or of this generic form “at least one of a, b, or c”, with more or less elements than “a”, “b”, and “c”. In either phrasing, the phrases are to be interpreted identically. In particular, “at least one of a, b, and c” is equivalent to “at least one of a, b, or c” and shall mean a, b, and/or c. As an example, it means: “a” only, “b” only, “c” only, “a” and “b”, “a” and “c”, “b” and “c”, and/or “a”, “b”, and “c”. 
     As may also be used herein, the terms “processing module”, “processing circuit”, “processor”, “processing circuitry”, and/or “processing unit” may be a single processing device or a plurality of processing devices. Such a processing device may be a microprocessor, micro-controller, digital signal processor, microcomputer, central processing unit, field programmable gate array, programmable logic device, state machine, logic circuitry, analog circuitry, digital circuitry, and/or any device that manipulates signals (analog and/or digital) based on hard coding of the circuitry and/or operational instructions. The processing module, module, processing circuit, processing circuitry, and/or processing unit may be, or further include, memory and/or an integrated memory element, which may be a single memory device, a plurality of memory devices, and/or embedded circuitry of another processing module, module, processing circuit, processing circuitry, and/or processing unit. Such a memory device may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and/or any device that stores digital information. Note that if the processing module, module, processing circuit, processing circuitry, and/or processing unit includes more than one processing device, the processing devices may be centrally located (e.g., directly coupled together via a wired and/or wireless bus structure) or may be distributedly located (e.g., cloud computing via indirect coupling via a local area network and/or a wide area network). Further note that if the processing module, module, processing circuit, processing circuitry and/or processing unit implements one or more of its functions via a state machine, analog circuitry, digital circuitry, and/or logic circuitry, the memory and/or memory element storing the corresponding operational instructions may be embedded within, or external to, the circuitry comprising the state machine, analog circuitry, digital circuitry, and/or logic circuitry. Still further note that, the memory element may store, and the processing module, module, processing circuit, processing circuitry and/or processing unit executes, hard coded and/or operational instructions corresponding to at least some of the steps and/or functions illustrated in one or more of the Figures. Such a memory device or memory element can be included in an article of manufacture. 
     One or more embodiments have been described above with the aid of method steps illustrating the performance of specified functions and relationships thereof. The boundaries and sequence of these functional building blocks and method steps have been arbitrarily defined herein for convenience of description. Alternate boundaries and sequences can be defined so long as the specified functions and relationships are appropriately performed. Any such alternate boundaries or sequences are thus within the scope and spirit of the claims. Further, the boundaries of these functional building blocks have been arbitrarily defined for convenience of description. Alternate boundaries could be defined as long as the certain significant functions are appropriately performed. Similarly, flow diagram blocks may also have been arbitrarily defined herein to illustrate certain significant functionality. 
     To the extent used, the flow diagram block boundaries and sequence could have been defined otherwise and still perform the certain significant functionality. Such alternate definitions of both functional building blocks and flow diagram blocks and sequences are thus within the scope and spirit of the claims. One of average skill in the art will also recognize that the functional building blocks, and other illustrative blocks, modules and components herein, can be implemented as illustrated or by discrete components, application specific integrated circuits, processors executing appropriate software and the like or any combination thereof. 
     In addition, a flow diagram may include a “start” and/or “continue” indication. The “start” and “continue” indications reflect that the steps presented can optionally be incorporated in or otherwise used in conjunction with one or more other routines. In addition, a flow diagram may include an “end” and/or “continue” indication. The “end” and/or “continue” indications reflect that the steps presented can end as described and shown or optionally be incorporated in or otherwise used in conjunction with one or more other routines. In this context, “start” indicates the beginning of the first step presented and may be preceded by other activities not specifically shown. Further, the “continue” indication reflects that the steps presented may be performed multiple times and/or may be succeeded by other activities not specifically shown. Further, while a flow diagram indicates a particular ordering of steps, other orderings are likewise possible provided that the principles of causality are maintained. 
     The one or more embodiments are used herein to illustrate one or more aspects, one or more features, one or more concepts, and/or one or more examples. A physical embodiment of an apparatus, an article of manufacture, a machine, and/or of a process may include one or more of the aspects, features, concepts, examples, etc. described with reference to one or more of the embodiments discussed herein. Further, from figure to figure, the embodiments may incorporate the same or similarly named functions, steps, modules, etc. that may use the same or different reference numbers and, as such, the functions, steps, modules, etc. may be the same or similar functions, steps, modules, etc. or different ones. 
     Unless specifically stated to the contra, signals to, from, and/or between elements in a figure of any of the figures presented herein may be analog or digital, continuous time or discrete time, and single-ended or differential. For instance, if a signal path is shown as a single-ended path, it also represents a differential signal path. Similarly, if a signal path is shown as a differential path, it also represents a single-ended signal path. While one or more particular architectures are described herein, other architectures can likewise be implemented that use one or more data buses not expressly shown, direct connectivity between elements, and/or indirect coupling between other elements as recognized by one of average skill in the art. 
     The term “module” is used in the description of one or more of the embodiments. A module implements one or more functions via a device such as a processor or other processing device or other hardware that may include or operate in association with a memory that stores operational instructions. A module may operate independently and/or in conjunction with software and/or firmware. As also used herein, a module may contain one or more sub-modules, each of which may be one or more modules. 
     As may further be used herein, a computer readable memory includes one or more memory elements. A memory element may be a separate memory device, multiple memory devices, or a set of memory locations within a memory device. Such a memory device may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and/or any device that stores digital information. The memory device may be in a form a solid-state memory, a hard drive memory, cloud memory, thumb drive, server memory, computing device memory, and/or other physical medium for storing digital information. 
     While particular combinations of various functions and features of the one or more embodiments have been expressly described herein, other combinations of these features and functions are likewise possible. The present disclosure is not limited by the particular examples disclosed herein and expressly incorporates these other combinations.