Abstract:
A method includes sending a data retrieval request regarding a data segment of a data object to redundant array of independent disk (RAID) memory and to dispersed storage network (DSN) memory. The method further includes receiving a first read response from a first one of the RAID memory and the DSN memory. The method further comprises recovering the data segment from the first read response. The method further includes determining whether to wait for a second read response from a second one of the RAID memory and the DSN memory. When the computing device determines to wait, the method further includes receiving the second response within a given time frame. The method further includes recovering a copy of the data segment from the second read response. When the data segment substantially matches the copy of the data segment, the method further includes utilizing either the data segment or the copy of the data segment.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
       [0001]    The present U.S. Utility Patent Application claims priority pursuant to 35 U.S.C. §120 as a continuation-in-part of U.S. Utility application Ser. No. 13/270,528, entitled “COMPACTING DISPERSED STORAGE SPACE”, filed Oct. 11, 2011, which claims priority pursuant to 35 U.S.C. §119(e) to U.S. Provisional Application No. 61/408,980, entitled “DISPERSED STORAGE NETWORK COMMUNICATION”, filed Nov. 1, 2010, both 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 
       [0002]    Not applicable. 
       INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC 
       [0003]    Not applicable. 
       BACKGROUND OF THE INVENTION 
       [0004]    Technical Field of the Invention 
         [0005]    This invention relates generally to computer networks and more particularly to dispersing error encoded data. 
         [0006]    Description of Related Art 
         [0007]    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. 
         [0008]    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. 
         [0009]    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. Improving the writing of data to and the reading of data from cloud storage is an on-going challenge. 
     
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S) 
         [0010]      FIG. 1  is a schematic block diagram of an embodiment of a dispersed or distributed storage network (DSN) in accordance with the present invention; 
           [0011]      FIG. 2  is a schematic block diagram of an embodiment of a computing core in accordance with the present invention; 
           [0012]      FIG. 3  is a schematic block diagram of an example of dispersed storage error encoding of data in accordance with the present invention; 
           [0013]      FIG. 4  is a schematic block diagram of a generic example of an error encoding function in accordance with the present invention; 
           [0014]      FIG. 5  is a schematic block diagram of a specific example of an error encoding function in accordance with the present invention; 
           [0015]      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; 
           [0016]      FIG. 7  is a schematic block diagram of an example of dispersed storage error decoding of data in accordance with the present invention; 
           [0017]      FIG. 8  is a schematic block diagram of a generic example of an error decoding function in accordance with the present invention; 
           [0018]      FIG. 9  is a schematic block diagram of an embodiment of a storage system that stores data utilizing a redundant array of independent discs (RAID) method and/or a distributed storage method in accordance with the present invention; 
           [0019]      FIG. 10  is a logic diagram of an example of a method of multiple memory format storage in accordance with the present invention; 
           [0020]      FIG. 11  is a logic diagram of another example of a method of multiple memory format storage in accordance with the present invention; 
           [0021]      FIG. 12  is a logic diagram of another example of a method of multiple memory format storage in accordance with the present invention; 
           [0022]      FIG. 13  is a logic diagram of another example of a method of multiple memory format storage in accordance with the present invention; and 
           [0023]      FIG. 14  is a logic diagram of another example of a method of multiple memory format storage in accordance with the present invention. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0024]      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 internet systems; and/or one or more local area networks (LAN) and/or wide area networks (WAN). 
         [0025]    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. 
         [0026]    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 . 
         [0027]    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 . 
         [0028]    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). 
         [0029]    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 . 
         [0030]    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. 
         [0031]    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. 
         [0032]    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 . 
         [0033]    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 . 
         [0034]      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 . 
         [0035]    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. 
         [0036]      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.). 
         [0037]    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. 
         [0038]    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. 
         [0039]      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 (D 1 -D 12 ). The coded matrix includes five rows of coded data blocks, where the first row of X 11 -X 14  corresponds to a first encoded data slice (EDS  1 _ 1 ), the second row of X 21 -X 24  corresponds to a second encoded data slice (EDS  2 _ 1 ), the third row of X 31 -X 34  corresponds to a third encoded data slice (EDS  3 _ 1 ), the fourth row of X 41 -X 44  corresponds to a fourth encoded data slice (EDS  4 _ 1 ), and the fifth row of X 51 -X 54  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. 
         [0040]    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 . 
         [0041]    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. 
         [0042]      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. 
         [0043]    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. 
         [0044]      FIG. 9  is another schematic block diagram of another embodiment of a storage system that stores data utilizing a redundant array of independent discs (RAID) method and/or a distributed storage method. The system includes at least one user device  12 , at least one RAID memory  400 , and at least one dispersed storage network (DSN) memory  22 . The DSN memory  22  may include a plurality of dispersed storage (DS) units  36 , wherein the DS units may be deployed at one or more sites. The RAID memory  400  may include a plurality of RAID units  402 . The RAID units  402  may have an associated memory and/or memory element which may be a single memory device or a plurality of memory devices to store portions of the RAID data. The memory device may be a read-only memory, a read-write memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, a magnetic disk drive, and/or any device that stores digital information. For example, the RAID memory  400  may include five RAID units  402 , wherein each of the five RAID units  402  includes a magnetic disk drive. 
         [0045]    The user device  12  or  16  may include a computing core  26  and a dispersed storage network interface  32 . The computing core  26  includes a DS processing  34  and a RAID controller  404 . The RAID controller  404  creates RAID data  406  in accordance with a RAID method based on data provided by the computing core  26 , wherein the data provided by the computing core may include one or more of data in a format of data blocks, data objects, and data files in accordance with a file system. The data provided by the computing core  26  may include data that is referenced by one or more of a data object name, a file name, a block number, a data object identifier (ID), and a file ID. The data provided by the computing core  26  may be described in part by metadata where the metadata may include one or more of a data type, a data size, a priority indicator, a security indicator, a performance indicator, a user ID, a group ID, a timestamp, and other descriptors to describe the data. For example, the RAID data  406  includes data and the metadata that describes the data. 
         [0046]    In an example of operation, the RAID controller  404  controls the RAID memory  400 . The RAID controller  404  produces RAID data  406  that includes commands, memory information, status information, and/or requests. For example, the commands include one or more of write, read, delete, status, erase, and invert. The memory information may include physical addresses utilized within the RAID memory. For example, the RAID controller order for may send the data of a text file, the metadata of the text file, and a store command to the RAID memory  400  to store the data and the metadata in the RAID memory  400 . The RAID method may include an approach to produce RAID data based in part on the data to be stored. 
         [0047]    The RAID data  406  may include RAID blocks, wherein the RAID blocks include data and/or parity information. The RAID method approach may include dividing the data object into blocks, determining parity information based on the blocks, producing RAID blocks based on the data blocks and the parity information to produce a data stripe, and determining which RAID blocks to store in which RAID units  402  of the RAID memory  400 . For example, the RAID controller  404  may store RAID blocks based of the data object in a first RAID unit  402  and may store RAID blocks based on the parity information in a second RAID unit  402  of the RAID memory  400  in accordance with the RAID method. As another example, the RAID controller  404  may store RAID blocks that include both data object data and parity information in a first RAID unit  402  of the RAID memory  400  in accordance with the RAID method. As yet another example, the RAID controller  404  may store a first RAID block in two or more RAID units  402 . 
         [0048]    The user device  12  may transform the data to generate RAID data  406  for storage in the RAID memory and/or may dispersed storage error encode the data to produce encoded data slices  11  for storage in the DSN memory  22 . For example, the user device  12  transforms the data into RAID data  406  and sends the RAID data  406  to the RAID memory  400  for storage but does not encode the data to produce slices. As another example, the user device  12  dispersed storage error encodes the data to produce encoded data slices  11  and sends the encoded data slices  11  to the DSN memory  22  for storage but does not transform the data to generate RAID data  406 . As yet another example, the user device  12  transforms the data into RAID data  406  and sends the RAID data  406  to the RAID memory  400  for storage and user device  12  dispersed storage error encodes the data to produce encoded data slices  11  and sends the encoded data slices  11  to the DSN memory  22  for storage. As such, the user device  12  stores the data in both the RAID memory  400  and the DSN memory  22 . 
         [0049]    As another example of operation, the DS processing  34  sends RAID data  406  (e.g., including a store and/or retrieve RAID data command) to the RAID memory  400  to store/retrieve RAID data  406  to/from the RAID memory  400 . In such an example, the DS processing  34  communicates with substantially the same commands as the RAID controller  404  with the RAID memory  400 . In an instance, the DS processing  34  receives RAID data  406  from the RAID memory  400  and transforms the RAID data  406  into data. In another instance, the DS processing  34  transforms data into RAID data  406  and sends the RAID data  406  to the RAID memory  400  for storage. 
         [0050]    As yet another example of operation, a processing module of the user device  12  stores the same data as RAID data  406  in the RAID memory  400  and as slices  11  in the DSN memory  22 . In a retrieval example of operation, the processing module attempts to retrieve the data by retrieving the RAID data  406  from the RAID memory  400 . Next, the processing module retrieves slices  11  from the DSN memory  22  to decode and reproduce the data when the processing module cannot successfully transform the RAID data  406  into the data. As another retrieval example of operation, the processing module attempts to retrieve the data by retrieving slices  11  from the DSN memory  22  and decoding the slices  11  to produce the data. Next, the processing module retrieves the data by retrieving the RAID data  406  from the RAID memory  22  when the processing module cannot successfully decode the slices  11  into the data. As yet another retrieval example of operation, the processing module retrieves slices  11  from the DSN memory  22  and decodes the slices to produce first data and the processing module retrieves the RAID data  406  from the RAID memory  400  and transforms the RAID data  406  into second data. Next, the processing module validates both the first data and the second data when the processing module determines that the first data is substantially the same as the second data. 
         [0051]      FIG. 10  is another flowchart illustrating another example of storing data. The method begins with step  262  where a processing module receives data to store. The method continues at step  410  where the processing module determines available memory, wherein available memory may include a redundant array of independent discs (RAID) memory and a dispersed storage network (DSN) memory. The determination may be based on one or more of a query, a message, a look up, and a command. 
         [0052]    The method continues at step  412  where the processing module determines whether RAID memory is available based on the determination of available memory. The method branches to step  418  when the processing module determines that the RAID memory is not available. The method continues to step  414  when the processing module determines that the RAID memory is available. The method continues at step  414  where the processing module transforms the data to create RAID data. The method continues at step  416  where the processing module facilitates storing the RAID data in the RAID memory. 
         [0053]    The method continues at step  418  where the processing module determines whether DSN memory is available based on the determination of available memory. The method branches to step  422  when the processing module determines that the DSN memory is available. The method ends at step  420  when the processing module determines that the DSN memory is not available. The method continues at step  422  where the processing module dispersed storage error encodes the data to produce a plurality of sets of encoded data slices. The method continues at step  424  where the processing module sends the plurality of sets of encoded data slices to the DSN memory for storage therein. 
         [0054]      FIG. 11  is a flowchart illustrating an example of retrieving data. The method begins with step  426  where a processing module (e.g., a dispersed storage (DS) processing unit) receives a data retrieval request message. The data retrieval request message may include one or more of a data identifier, a source name, one or more slice names, a virtual dispersed storage network (DSN) address, a memory identifier, a priority indicator, a security indicator, a performance indicator, a user identifier (ID), and a retrieval request command. The method continues at step  428  where the processing module facilitates retrieving the data from a redundant array of independent disks (RAID) memory based on information received in the data retrieval request message. 
         [0055]    The method continues at step  430  where the processing module determines whether the data is successfully retrieved from the RAID memory. The determination may be based on one or more of the data, a stored data size indicator, a measured data size, calculating a calculated integrity check value, receiving a stored integrity check value, and comparing the calculated integrity check value to the stored integrity check value. For example, the processing module determines that the data is successfully retrieved when the stored integrity check value compares favorably to the calculated integrity check value. The method branches to step  434  when the processing module determines that the data is not successfully retrieved from the RAID memory. The method ends at step  432  when the processing module determines that the data is successfully retrieved from the RAID memory. 
         [0056]    The method continues at step  434  where the processing module retrieves the threshold number of encoded data slices corresponding to each of a plurality of sets of encoded data slices corresponding to the data from a DSN memory. The method continues at step  436  where the processing module dispersed storage error decodes the threshold number of encoded data slices corresponding to each of the plurality of sets of encoded data slices to reproduce the data. 
         [0057]      FIG. 12  is another flowchart illustrating another example of retrieving data. The method begins with step  426  where a processing module receives a data retrieval request. The method continues at step  440  where the processing module retrieves a threshold number of encoded data slices corresponding to each of a plurality of sets of encoded data slices corresponding to the data from a dispersed storage network (DSN) memory. The threshold number of slices may not be received due to one or more of errors, a network failure, a dispersed storage (DS) unit failure, and any other error preventing the retrieval of the slices. 
         [0058]    The method continues at step  442  where the processing module dispersed storage error decodes the threshold number of encoded data slices corresponding to each of the plurality of sets of encoded data slices to reproduce the data. The method continues at step  444  where the processing module determines whether the data is successfully retrieved from the DSN memory. The determination may be based on one or more of the data, validated encoded data slices, a stored data size indicator, a measured data size, calculating a calculated integrity check value, receiving a stored integrity check value, and comparing the calculated integrity check value to the stored integrity check value. For example, the processing module determines that the data is successfully retrieved when the stored integrity check value compares favorably to the calculated integrity check value. The method branches to step  448  when the processing module determines that the data is not successfully retrieved from the DSN memory. The method ends at step  446  when the processing module determines that the data is successfully retrieved from the DSN memory. The method continues at step  448  where the processing module facilitates retrieving the data from a RAID memory. 
         [0059]      FIG. 13  is another flowchart illustrating another example of retrieving data. The method begins with step  426  where a processing module receives a data retrieval request. The method continues with step  450  where the processing module sends redundant array of independent disks (RAID) data to a RAID memory to facilitate retrieving the data. The method continues at step  452  where the processing module sends at least a threshold number of retrieve slice request messages to at least a threshold number of dispersed storage (DS) units of a dispersed storage network (DSN) memory wherein at least some of the plurality of sets of encoded data slices corresponding to the data are stored. 
         [0060]    The method continues with step  454  where the processing module determines sourcing of the data by determining whether the data is received from the RAID memory or whether data is received as a threshold number of encoded data slices from the DSN memory corresponding to each of the plurality of sets of encoded data slices facilitating decoding the threshold number of encoded data slices to produce the data. For example, the data is received from the RAID memory first. As another example, the data is received from the DSN memory first. The method branches to step  456  where the processing module utilizes the data from the DSN memory when the processing module determines that a first received source is the DSN memory. The method continues to step  458  when the processing module determines that the first received source is the RAID memory. The method continues at step  458  where the processing module utilizes the data from the RAID memory as the data. The method continues at step  456  where the processing module utilizes the data from the DSN memory as the data when the processing module determines that the first received source is the DSN memory. 
         [0061]      FIG. 14  is another flowchart illustrating another example of retrieving data. The method begins with step  426  where a processing module receives a data retrieval request. The method continues at step  460  where the processing module facilitates retrieving the data from a redundant array of independent disks (RAID) data memory to produce first data. The method continues at step  440  where the processing module retrieves a threshold number of encoded data slices corresponding to each of a plurality of sets of encoded data slices corresponding to the data from a dispersed storage network (DSN) memory. The method continues at step  462  where the processing module dispersed storage error decodes the threshold number of encoded data slices corresponding to each of the plurality of sets of encoded data slices to produce second data. 
         [0062]    The method continues at step  464  where the processing module determines whether the first data and the second data are substantially the same. The method branches to step  468  when the processing module determines that the first data and the second data are substantially the same. The method continues to step  466  when the processing module determines that the first data and the second data are not substantially the same. The method continues at step  466  where the processing module sends an error message. The error message may include one or more of an indication that the first data and the second data are not substantially the same, a RAID memory identifier, a DSN memory identifier, a data identifier, the user identifier, one or more slice names, a source name, and an error code. The processing module may send the error message to one or more of a dispersed storage (DS) managing unit, a DS unit, a DS processing unit, a user device, a requester, and a storage integrity processing unit. The method continues at step  468  where the processing module utilizes the first data as the data when the processing module determines that the first and second data are substantially the same. Alternatively, the processing module utilizes the second data as the data when the processing module determines that the first and second data are substantially the same. 
         [0063]    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, audio, etc. any of which may generally be referred to as ‘data’). 
         [0064]    As may be used herein, the terms “substantially” and “approximately” provides an industry-accepted tolerance for its corresponding term and/or relativity between items. Such an industry-accepted tolerance ranges from less than one percent to fifty percent and corresponds to, but is not limited to, component values, integrated circuit process variations, temperature variations, rise and fall times, and/or thermal noise. Such relativity between items ranges from a difference of a few percent to magnitude 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. 
         [0065]    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. 
         [0066]    As may also be used herein, the terms “processing module”, “processing circuit”, “processor”, 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, 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, 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, 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, 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, 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. 
         [0067]    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. 
         [0068]    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. 
         [0069]    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 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. 
         [0070]    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. 
         [0071]    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. 
         [0072]    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. 
         [0073]    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. 
         [0074]    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.