Patent Publication Number: US-2022236870-A1

Title: Method and system for compression in block-based storage systems

Description:
BACKGROUND 
     Technical Field 
     This application relates to compression in block-based storage systems. 
     Description of Related Art 
     Computer systems may include different resources used by one or more host processors. Resources and host processors in a computer system may be interconnected by one or more communication connections. These resources may include, for example, data storage devices. These data storage systems may be coupled to one or more servers or host processors and provide storage services to each host processor. Multiple data storage systems from one or more different vendors may be connected and may provide common data storage for one or more host processors in a computer system. 
     A host processor may perform a variety of data processing tasks and operations using the data storage system. For example, a host processor may perform basic system I/O operations in connection with data requests, such as data read and write operations. 
     Host processor systems may store and retrieve data using a storage device containing a plurality of host interface units, disk drives, and disk interface units. The host systems access the storage device through a plurality of channels provided therewith. Host systems provide data and access control information through the channels to the storage device and the storage device provides data to the host systems also through the channels. The host systems do not address the disk drives of the storage device directly, but rather, access what appears to the host systems as a plurality of logical disk units. The logical disk units may or may not correspond to the actual disk drives. Allowing multiple host systems to access the single storage device unit allows the host systems to share data in the device. In order to facilitate sharing of the data on the device, additional software on the data storage systems may also be used. 
     Such a data storage system typically includes processing circuitry and a set of drives (disk drives are also referred to herein as simply “disks” or “drives”). In general, the processing circuitry performs load and store operations on the set of drives on behalf of the host devices. In certain data storage systems, the drives of the data storage system are distributed among one or more separate drive enclosures (disk drive enclosures are also referred to herein as “disk arrays” or “storage arrays”) and processing circuitry serves as a front-end to the drive enclosures. The processing circuitry presents the drive enclosures to the host device as a single, logical storage location and allows the host device to access the drives such that the individual drives and drive enclosures are transparent to the host device. 
     Storage arrays are typically used to provide storage space for one or more computer file systems, databases, applications, and the like. For this and other reasons, it is common for storage arrays to be structured into logical partitions of storage space, called logical units (also referred to herein as LUs or LUNs). For example, at LUN creation time, storage system may allocate storage space of various storage devices to be presented as a logical volume for use by an external host device. This allows a storage array to appear as a collection of separate file systems, network drives, and/or volumes. 
     Some data storage systems employ software compression and decompression to improve storage efficiency. For example, software compression involves loading compression instructions into memory and executing the instructions on stored data using one or more processing cores. A result of such software compression is that compressed data requires less storage space than the original, uncompressed data. Conversely, software decompression involves loading decompression instructions into the memory and executing the instructions on the compressed data using one or more of the processing cores, to restore the compressed data to its original, uncompressed form. 
     Other data storage systems perform compression and decompression in hardware. For example, a data storage system may include specialized hardware for compressing and decompressing data. The specialized hardware may be provided on the storage processor itself, e.g., as a chip, chipset, or sub-assembly, or on a separate circuit board assembly. Unlike software compression, which operates by running executable software instructions on a computer, hardware compression employs one or more ASICs (Application Specific Integrated Circuits), FPGAs (Field Programmable Gate Arrays), RISC (Reduced Instruction Set Computing) processors, and/or other specialized devices in which operations may be hard-coded and performed at high speed. 
     SUMMARY OF THE INVENTION 
     One aspect of the current technique is a method for dictionary-based compression in block-based storage systems. The method includes identifying, by a processor of the block-based storage system, a stored block of data that is similar to a received block of data. The method also includes determining a dictionary based on the stored block of data. The method further includes compressing the received block of data based on the dictionary based on the stored block of data. The method also includes storing the compressed, received block of data with an association to the stored block of data. 
     The method may determine a similarity hash value of the received block of data, and compare the similarity hash value of the received block of data to similarity hash values of stored blocks of data. The method may select a stored block of data whose similarity hash value falls within a threshold of the similarity hash value of the received block of data. The method may create a dictionary based on the stored block of data, or use the stored block of data as raw data for the dictionary. 
     Another aspect of the current technique is a system, with a processor, for dictionary-based compression in block-based storage systems. The processor is configured to identify a stored block of data that is similar to a received block of data; determine a dictionary based on the stored block of data; compress the received block of data based on the dictionary based on the stored block of data; and store the compressed, received block of data with an association to the stored block of data. The processor may be configured to perform any other processes in conformance with the aspect of the current technique described above. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Features and advantages of the present technique will become more apparent from the following detailed description of exemplary embodiments thereof taken in conjunction with the accompanying drawings in which: 
         FIG. 1  depicts an exemplary embodiment of a computer system that may utilize the techniques described herein; 
         FIG. 2  depicts an exemplary embodiment of a data storage system used in the computer system of  FIG. 1 ; 
         FIG. 3  depicts a schematic diagram of data blocks as compressed and stored on a data storage device of the data storage system of  FIG. 1 , according to dictionary-based compression techniques described herein; and 
         FIGS. 4-6  are exemplary flow diagrams of methods for dictionary-based compression in a block-based storage system. 
     
    
    
     DETAILED DESCRIPTION OF EMBODIMENT(S) 
     Described below is a technique for compression in a block-based storage system, which technique may be used to provide, among other things, identifying a stored block of data that is similar to a received block of data; determining a dictionary based on the stored block of data; compressing the received block of data based on the dictionary based on the stored block of data; and storing the compressed, received block of data with an association to the stored block of data. 
     Data compression is an efficiency feature that allows users to store information using less storage capacity than storage capacity used without compression. With data compression, users can significantly increase storage utilization. Compression may be characterized as the process of encoding source information using an encoding scheme into a compressed form having fewer bits than the original or source information. Many techniques for compression leverage redundancy within the data. For example, data may include multiple instances of the same sequence of bytes. Replacing each instance with the same, shorter representation reduces the overall amount of data stored. 
     One exemplary type of encoding scheme uses dictionaries. A file-based storage system may create a dictionary based on data in a designated portion of storage, such as a file, folder, page, drive, or volume. For example, the storage system may create a dictionary for a file by analyzing its data, identifying redundant byte sequences, and associating each unique byte sequence with a distinct symbol. To compress the file using the dictionary, each byte sequence in the file that also appears in the dictionary is replaced with its corresponding symbol. The storage system may store both the file and its dictionary in persistent memory. When the storage system receives a request to read the file, the storage system may identify the dictionary to decompress the file, and load the file along with its dictionary. The file may be decompressed by replacing each instance of a dictionary symbol with its corresponding byte sequence. 
     Because the file-based storage system uses different dictionaries for different portions of storage, numerous dictionaries must be created and stored. Given the level of redundancy often present in known portions of storage (e.g., files, pages), dictionary-based compression techniques often use at least a 32 KB window for identifying redundant byte sequences. Furthermore, these compression techniques may accommodate large dictionaries, such as those that are 100 KB or larger, because of the reductions in data attained. 
     However, conventional dictionary-based compression techniques are inapplicable to block-based file systems, and do not yield the advantages that they reap in file-based storage systems. Some block-based file systems operate upon small blocks (e.g., 4 KB, 8 KB), which limit the windows that compression algorithms can use for identifying redundant byte sequences. Consequently, the limited window size diminishes the effectiveness of conventional compression techniques. 
     Furthermore, in some situations, a block-based storage system may service random read requests for small amounts of data. In a file-based storage system, when data resides on different portions of storage (e.g., pages, drives), the dictionary for each portion must be loaded to process the requests. As explained above, any given dictionary may be large, and the file-based system may have numerous dictionaries. However, in a block-based storage system, repeatedly loading large dictionaries to service read requests of small amounts of data consumes significant computing resources and hinders performance, such as input/output operations per second (IOPS). 
     Instead of creating dictionaries for predetermined portions of storage, compression techniques described herein create dictionaries for blocks based on their similarity. A block-based file system generates and stores similarity hash values for data blocks. When the file system receives a block, the file system determines its similarity hash value and uses this hash value to find a similar, stored block. A dictionary is created using the stored block, and the received block is compressed based on the dictionary. The compressed, received block is stored with a reference to the similar, stored block. Thus, when the compressed, received block is subsequently read, the block can be decompressed based on the similar block. 
     Furthermore, the compression techniques described herein may be used in combination with non-dictionary-based compression. Received blocks may also be compressed based on conventional compression, and the results may be compared against the dictionary-compressed versions of the blocks. Since the superior result is stored, dictionaries may not be retained if they do not yield results that are advantageous over other compression techniques. 
     In at least some implementations in accordance with the compression techniques as described herein, the use of dictionary-based compression in block-based storage systems can provide one or more of the following advantages: improved input/output operations per second (IOPS) performance, particularly for random read requests of small amounts of data (e.g., on the order of 4 KB); support of numerous dictionaries without corresponding sacrifice in performance; support for dictionaries of arbitrary block content; and reduced persistent memory required to store the dictionaries. 
       FIG. 1  depicts an example embodiment of a computer system  10  that may be used in connection with performing the techniques described herein. The system  10  includes one or more data storage systems  12  connected to server or hosts  14   a - 14   n  through communication medium  18 . The system  10  also includes a management system  16  connected to one or more data storage systems  12  through communication medium  20 . In this embodiment of the system  10 , the management system  16 , and the N servers or hosts  14   a - 14   n  may access the data storage systems  12 , for example, in performing input/output (I/O) operations, data requests, and other operations. The communication medium  18  may be any one or more of a variety of networks or other type of communication connections as known to those skilled in the art. Each of the communication mediums  18  and  20  may be a network connection, bus, and/or other type of data link, such as a hardwire or other connections known in the art. For example, the communication medium  18  may be the Internet, an intranet, network or other wireless or other hardwired connection(s) by which the hosts  14   a - 14   n  may access and communicate with the data storage systems  12 , and may also communicate with other components (not shown) that may be included in the system  10 . In one embodiment, the communication medium  20  may be a LAN connection and the communication medium  18  may be an iSCSI, Fibre Channel, Serial Attached SCSI, or Fibre Channel over Ethernet connection. 
     Each of the hosts  14   a - 14   n  and the data storage systems  12  included in the system  10  may be connected to the communication medium  18  by any one of a variety of connections as may be provided and supported in accordance with the type of communication medium  18 . Similarly, the management system  16  may be connected to the communication medium  20  by any one of variety of connections in accordance with the type of communication medium  20 . The processors included in the hosts  14   a - 14   n  and management system  16  may be any one of a variety of proprietary or commercially available single or multi-processor system, or other type of commercially available processor able to support traffic in accordance with any embodiments described herein. 
     It should be noted that the particular examples of the hardware and software that may be included in the data storage systems  12  are described herein in more detail, and may vary with each particular embodiment. Each of the hosts  14   a - 14   n , the management system  16  and data storage systems  12  may all be located at the same physical site, or, alternatively, may also be located in different physical locations. In connection with communication mediums  18  and  20 , a variety of different communication protocols may be used such as SCSI, Fibre Channel, iSCSI, and the like. Some or all of the connections by which the hosts  14   a - 14   n , management system  16 , and data storage systems  12  may be connected to their respective communication medium  18 ,  20  may pass through other communication devices, such as switching equipment that may exist such as a phone line, a repeater, a multiplexer or even a satellite. In one embodiment, the hosts  14   a - 14   n  may communicate with the data storage systems  12  over an iSCSI or a Fibre Channel connection and the management system  16  may communicate with the data storage systems  12  over a separate network connection using TCP/IP. It should be noted that although  FIG. 1  illustrates communications between the hosts  14   a - 14   n  and data storage systems  12  being over a first communication medium  18 , and communications between the management system  16  and the data storage systems  12  being over a second different communication medium  20 , other embodiments may use the same connection. The particular type and number of communication mediums and/or connections may vary in accordance with particulars of each embodiment. 
     Each of the hosts  14   a - 14   n  may perform different types of data operations in accordance with different types of tasks. In the embodiment of  FIG. 1 , any one of the hosts  14   a - 14   n  may issue a data request to the data storage systems  12  to perform a data operation. For example, an application executing on one of the hosts  14   a - 14   n  may perform a read or write operation resulting in one or more data requests to the data storage systems  12 . 
     The management system  16  may be used in connection with management of the data storage systems  12 . The management system  16  may include hardware and/or software components. The management system  16  may include one or more computer processors connected to one or more I/O devices such as, for example, a display or other output device, and an input device such as, for example, a keyboard, mouse, and the like. The management system  16  may, for example, display information about a current storage volume configuration, provision resources for a data storage system  12 , and the like. 
     Each of the data storage systems  12  may include one or more data storage devices  17   a - 17   n . Unless noted otherwise, data storage devices  17   a - 17   n  may be used interchangeably herein to refer to hard disk drive, solid state drives, and/or other known storage devices. One or more data storage devices  17   a - 17   n  may be manufactured by one or more different vendors. Each of the data storage systems included in  12  may be inter-connected (not shown). Additionally, the data storage systems  12  may also be connected to the hosts  14   a - 14   n  through any one or more communication connections that may vary with each particular embodiment. The type of communication connection used may vary with certain system parameters and requirements, such as those related to bandwidth and throughput required in accordance with a rate of I/O requests as may be issued by the hosts  14   a - 14   n , for example, to the data storage systems  12 . It should be noted that each of the data storage systems  12  may operate stand-alone, or may also be included as part of a storage area network (SAN) that includes, for example, other components such as other data storage systems  12 . The particular data storage systems  12  and examples as described herein for purposes of illustration should not be construed as a limitation. Other types of commercially available data storage systems  12 , as well as processors and hardware controlling access to these particular devices, may also be included in an embodiment. 
     In such an embodiment in which element  12  of  FIG. 1  is implemented using one or more data storage systems  12 , each of the data storage systems  12  may include code thereon for performing the techniques as described herein. 
     Servers or hosts, such as  14   a - 14   n , provide data and access control information through channels on the communication medium  18  to the data storage systems  12 , and the data storage systems  12  may also provide data to the host systems  14   a - 14   n  also through the channels  18 . The hosts  14   a - 14   n  may not address the disk drives of the data storage systems  12  directly, but rather access to data may be provided to one or more hosts  14   a - 14   n  from what the hosts  14   a - 14   n  view as a plurality of logical devices or logical volumes (LVs). The LVs may or may not correspond to the actual disk drives. For example, one or more LVs may reside on a single physical disk drive. Data in a single data storage system  12  may be accessed by multiple hosts  14   a - 14   n  allowing the hosts  14   a - 14   n  to share the data residing therein. An LV or LUN (logical unit number) may be used to refer to the foregoing logically defined devices or volumes. 
     The data storage system  12  may be a single unitary data storage system, such as single data storage array, including two storage processors  114 A,  114 B or computer processing units. Techniques herein may be more generally use in connection with any one or more data storage system  12  each including a different number of storage processors  114  than as illustrated herein. The data storage system  12  may include a data storage array  116 , including a plurality of data storage devices  17   a - 17   n  and two storage processors  114 A,  114 B. The storage processors  114 A,  114 B may include a central processing unit (CPU) and memory and ports (not shown) for communicating with one or more hosts  14   a - 14   n . The storage processors  114 A,  114 B may be communicatively coupled via a communication medium such as storage processor bus  19 . The storage processors  114 A,  114 B may be included in the data storage system  12  for processing requests and commands. In connection with performing techniques herein, an embodiment of the data storage system  12  may include multiple storage processors  114  including more than two storage processors as described. Additionally, the two storage processors  114 A,  114 B may be used in connection with failover processing when communicating with the management system  16 . Client software on the management system  16  may be used in connection with performing data storage system management by issuing commands to the data storage system  12  and/or receiving responses from the data storage system  12  over connection  20 . In one embodiment, the management system  16  may be a laptop or desktop computer system. 
     The particular data storage system  12  as described in this embodiment, or a particular device thereof, such as a disk, should not be construed as a limitation. Other types of commercially available data storage systems  12 , as well as processors and hardware controlling access to these particular devices, may also be included in an embodiment. 
     In some arrangements, the data storage system  12  provides block-based storage by storing the data in blocks of logical storage units (LUNs) or volumes and addressing the blocks using logical block addresses (LBAs). In other arrangements, the data storage system  12  provides file-based storage by storing data as files of a file system and locating file data using inode structures. In yet other arrangements, the data storage system  12  stores LUNs and file systems, stores file systems within LUNs, and so on. 
     The two storage processors  114 A,  114 B (also referred to herein as “SP”) may control the operation of the data storage system  12 . The processors may be configured to process requests as may be received from the hosts  14   a - 14   n , other data storage systems  12 , management system  16 , and other components connected thereto. Each of the storage processors  114 A,  114 B may process received requests and operate independently and concurrently with respect to the other processor. With respect to data storage management requests, operations, and the like, as may be received from a client, such as the management system  16  of  FIG. 1  in connection with the techniques herein, the client may interact with a designated one of the two storage processors  114 A,  114 B. Upon the occurrence of failure of one the storage processors  114 A,  114 B, the other remaining storage processors  114 A,  114 B may handle all processing typically performed by both storage processors  114 A. 
       FIG. 2  depicts an exemplary embodiment of a data storage system  12  used in the computer system  10  of  FIG. 1 . In addition to the storage processors  114 A,  114 B and data storage devices  17   a - 17   n  depicted in  FIG. 1 , the data storage system  12  can include a memory  122 . The memory  122  can include persistent memory (e.g., flash memory, magnetic memory) and non-persistent memory (e.g., dynamic random access memory (DRAM), static random access memory (SRAM)). 
     The memory  112  can store a table  205  of pointers  210   a ,  210   b , . . . ,  210   n  (collectively, “ 210 ”) to blocks in the data storage system  12  and their corresponding similarity hash values  215   a ,  215   b , . . . ,  215   n  (collectively, “ 215 ”). As the data storage system  12  receives data, the storage system  12  applies a similarity hash algorithm to determine the hash values  215  of the data blocks. In various embodiments, the similarity hash algorithm may be locality-sensitive hashing (LSH). The hash values  215  may be determined inline, or as part of a background process. The use of the hash values  215  to achieve dictionary-based compression will be described in more detail below. 
       FIG. 3  depicts a schematic diagram of data blocks  305   a ,  305   b  (collectively referred to herein as “ 305 ”) as compressed and stored on a data storage device  17  of the data storage system  12 , according to dictionary-based compression techniques described herein. After being compressed according to a dictionary based on a similar, previously stored block  315   a , a data block  305   a  is stored as compressed data  310   a . A pointer  210   a  to the similar block  315   a  (also referred to herein as a “dictionary block”) is stored in association with the compressed data  310   a.    
     When the data storage system  12  receives a data block  305   a , the storage system  12  determines whether a similar data block  315   a  has already been stored. The storage system  12  compares the similarity hash value  215  of the received data block  305   a  with the hash values  215  in the table  205 . If the data storage system  12  determines that no similar data blocks have been previously stored, the received data block  305   a  itself is stored and its pointer  210  and similarity hash value  215  are added to the table  205 . In some embodiments the received data block  305   a  may be compressed prior to storage. Exemplary compression algorithms include Deflate and Zstandard, although other algorithms may be used, as would be appreciated by one of ordinary skill in the art. 
     The table  205  may have a similarity hash value  215  that matches that of the received data block  305   a . If so, the data storage system  12  can identify a stored data block  315   a  with the same byte sequence as the received data block  305   a . However, the techniques described herein may be applied to data blocks  305 ,  315  that are similar, and the manner in which data blocks  305 ,  315  are identified as such may depend on attributes of the similarity hash algorithm being used. In some embodiments, the data storage system  12  identifies all hash values  215  in the table  205  within a threshold distance of the received data block&#39;s  305   a  hash value  215 , and selects the stored data block  315   a  corresponding to the minimum threshold distance. In other embodiments, once the data storage system  12  finds a hash value  215  within the threshold distance of the received data block&#39;s  305   a  hash value  215 , the data storage system  12  uses this stored data block  315   a  and does not search the remainder of the table  205 . 
     The storage system  12  retrieves the stored data block  315   a , and in some embodiments, decompresses the data. The storage system  12  uses the stored data block  315   a  to determine a dictionary for compressing the received block  305   a . The manner in which the dictionary is determined may depend on the non-dictionary-based compression algorithm being used. For example, if the data storage system  12  is compressing data using Deflate, the data in the stored block  315   a  may be used as a dictionary. For example, the stored block  315   a  may be loaded into a compressor as an input for the Deflate compression algorithm. However, if Zstandard is being used, the stored data block  315   a  may be used as raw data to create a dictionary. 
     The data storage system  12  may compress the received data block  305   a  according to the dictionary, and also compress the same data  305   a  using other compression techniques (e.g., Deflate, Zstandard). The compression results are compared, and if the dictionary-based result  310   a  is superior to the other result by a certain threshold (e.g., 10%, 20%), the dictionary-based compression result  310   a  is stored, along with a pointer  210   a  to the stored data block  315   a  upon which the dictionary is based. If the dictionary-based technique does not yield an adequately superior outcome, the data block compressed according to other technique(s) is stored. In this manner, the data storage system  12  may store data based on the compression technique that achieves greater reduction in overall storage, which may also account for the overhead incurred by referring to data blocks upon which dictionaries are retrieved. 
     In some embodiments, the storage system  12  executes the steps of decompressing the stored data block  315   a , creating a dictionary based on the stored data block  315   a , and compressing the received data block  305   a  based on the dictionary, in hardware. The hardware may perform all three steps using a single command. In other embodiments, the hardware may use separate commands to perform each of these steps. In some embodiments, when the data storage system  12  uses Deflate, such as the version implemented in the open source library zlib available at https://github.com/madler/zlib, exemplary code for implementing an embodiment of the dictionary-based compression techniques described herein may include:
         compressed_B=read(B)   raw_B=zlib.decompress(compressed_B)   zcompo=zlib.compressobj(zdict=raw_B)   zcomp.append(zcompo.compress(raw_A))   zcomp.append(zcompo.flush( ))       

     In further embodiments, when the data storage system  12  uses Zstandard, such as the version implemented in the open source library zstd available at https://github.com/facebook/zstd, exemplary code for implementing an embodiment of the dictionary-based compression techniques described herein may include:
         compressed_B=read(B)   dctx=zstd.ZstdDecompressor( )   raw_B=dctx.decompress(compressed_B)   dict_data=zstd.ZstdCompressionDict(raw_B, dict_type=zstd.DICT_TYPE_RAWCONTENT)   zctx=zstd.ZstdCompressor(dict_data=dict_data)   compress=zctx.compress(raw_A)       

     A data block  310   a  compressed according to techniques described herein is stored with a pointer  210   a  to another block  315   a , which forms the basis for the dictionary used to compress the data block (for clarity, the other block will be referred to as the “dictionary block”). If the dictionary block  315   a  has been stored in a compressed form, the storage system  12  decompresses the data. A dictionary is determined based on the dictionary block  315   a , and as in the write process, the manner in which this dictionary is determined may depend on the non-dictionary-based compression algorithm being used. Thus, the dictionary block  315   a  may be used as input to a decompression engine (e.g., when Deflate is being used), or used as raw data for a dictionary (e.g., when Zstandard is being used). Then, the data block  305   a  being read is decompressed using this dictionary. 
     In some embodiments, the storage system  12  executes the steps of decompressing the dictionary block  315   a , determining the dictionary based on the dictionary block  315   a , and decompressing the data block  310   a  based on the dictionary, in hardware. The hardware may perform all three steps using a single command. In other embodiments, the hardware may use separate commands to perform each of these steps. 
       FIG. 4  is an exemplary flow diagram  400  of a method for dictionary-based compression in a block-based storage system. The storage system  12  identifies a stored block of data that is similar to a received block of data (step  405 ). The storage system  12  determines a dictionary based on the stored block of data (step  410 ). The storage system  12  may decompress the stored block of data. The received block of data is compressed based on this dictionary (step  415 ), and the compressed data is stored with an association to the stored block of data (step  420 ). 
       FIG. 5  is an exemplary flow diagram  500  of another method for dictionary-based compression in a block-based storage system. The storage system  12  determines a similarity hash value of a received block of data (step  505 ), and identifies, based on the similarity hash value, a similar stored block of data (step  510 ). The storage system  12  determines a dictionary based on the stored block of data (step  515 ), and may decompress the stored block of data. The storage system  12  compresses the received block of data based on this dictionary (step  520 ), and stores the compressed data with an association to the stored block of data (step  525 ). 
       FIG. 6  is an exemplary flow diagram  600  of another method for dictionary-based compression in a block-based storage system. The storage system  12  retrieves a compressed data block and a pointer to a dictionary block (step  605 ), and retrieves the dictionary block (step  610 ). The storage system  12  may decompress the dictionary block. The storage system  12  determines a dictionary based on the dictionary block (step  615 ), and decompresses the compressed data block using the dictionary (step  620 ). 
     It should again be emphasized that the implementations described above are provided by way of illustration, and should not be construed as limiting the present invention to any specific embodiment or group of embodiments. For example, the invention can be implemented in other types of systems, using different arrangements of processing devices and processing operations. Also, message formats and communication protocols utilized may be varied in alternative embodiments. Moreover, various simplifying assumptions made above in the course of describing the illustrative embodiments should also be viewed as exemplary rather than as requirements or limitations of the invention. Numerous alternative embodiments within the scope of the appended claims will be readily apparent to those skilled in the art. 
     Furthermore, as will be appreciated by one skilled in the art, the present disclosure may be embodied as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, the present disclosure may take the form of a computer program product on a computer-usable storage medium having computer-usable program code embodied in the medium. 
     The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. 
     The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising”, when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. 
     While the invention has been disclosed in connection with preferred embodiments shown and described in detail, their modifications and improvements thereon will become readily apparent to those skilled in the art. Accordingly, the spirit and scope of the present invention should be limited only by the following claims.