Patent Publication Number: US-8996787-B2

Title: Storage device aware of I/O transaction and stored data

Description:
BACKGROUND 
     Storage devices, such as memory cards and solid-state drives, are written to and read from according to and based on commands that are received from a host device. For example, a host device can send a read command to the storage device to retrieve data and send a write command to the storage device to store data. In many situations, the host device sends a logical address with the read or write command, and a controller in the storage device translates the logical address to a physical address of the memory of the storage device. As a storage device often just responds to commands from the host device, the storage device is not aware of the type of data being read from or written to the storage device. 
     OVERVIEW 
     Embodiments of the present invention are defined by the claims, and nothing in this section should be taken as a limitation on those claims. 
     By way of introduction, the below embodiments relate to a storage device that is aware of I/O transactions and stored data. In one embodiment, a storage device identifies a type of data stored in each logical partition of the storage device. When the storage device receives a request from the host device to access a logical partition of the memory, the storage device handles the request based on the identified type of data stored in the logical partition. 
     Other embodiments are possible, and each of the embodiments can be used alone or together in combination. Accordingly, various embodiments will now be described with reference to the attached drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram of an exemplary host device and storage device of an embodiment. 
         FIG. 2  is a block diagram of an exemplary host device and storage device of an embodiment. 
         FIG. 3  is a flow chart of a detection process of an embodiment. 
         FIG. 4  is a flow chart of a process to detect and analyze usages of physical partitions of an embodiment. 
         FIG. 5  is a flow chart of a process to detect and analyze usages of logical partitions of an embodiment. 
         FIG. 6  is a flow chart of a process of identifying logical partition layouts of an embodiment. 
         FIG. 7  is a flow chart of a process for parsing a UEFI system partition GUID of an embodiment. 
         FIG. 8  is a flow chart of a process for parsing a logical partition of an embodiment. 
         FIG. 9  is a flow chart of a process for parsing FAT32 vital information of an embodiment. 
         FIG. 10  is a flow chart for performing risk analysis of an embodiment. 
         FIG. 11  is a flow chart for performing boot partition risk analysis of an embodiment. 
         FIG. 12  is a flow chart for performing risk analysis of a GPT area of an embodiment. 
         FIG. 13  is a flow chart for determining a rule violation of an embodiment. 
         FIG. 14  is a flow chart for performing data compression analysis of an embodiment. 
         FIG. 15  is a flow chart for detecting a success probability for selective data compression of an embodiment. 
         FIG. 16  is a flow chart for detecting a success probability for static selective data compression of an embodiment. 
         FIG. 17  is a flow chart for detecting a success probability for dynamic selective data compression of an embodiment. 
     
    
    
     DETAILED DESCRIPTION OF THE PRESENTLY PREFERRED EMBODIMENTS 
     General Overview 
     There are several embodiment disclosed herein, which can be used alone or together in combination. One embodiment relates to a storage device that is aware of I/O transactions and stored data. As mentioned in the background section, data in many of today&#39;s storage devices is typically written to/read from the storage device according to and based on commands that are received from the host device, regardless of the characteristics and meaning of the information being stored. This embodiment uses various detection mechanisms to determine relevant information and uses that information to optimize host requests handling. This can enable a storage device to alter its behavior based on knowledge driven by the data stored on it, how this data is stored and accessed (e.g., write/read patterns), and prior system knowledge. This allows the storage device to optimize its operation and achieve higher reliability without involving the host device. 
     Another embodiment is directed to a storage device and method for utilizing unused storage space. Storage devices today may contain storage space which, in high probability, will not be used during the lifetime of the storage device. In this embodiment, the storage device uses already-retrieved knowledge on data being transferred to/from it as well as the way this data is being transferred (e.g. protocol, pattern, etc.) to identify non-active storage areas in the memory that, in high probability, will not be used. This provides the storage device with the ability to better exploit unused user storage areas in the memory, which may optimize storage behavior and improve reliability and performance of the device. 
     Yet another embodiment is directed to a storage device and method for selective data compression. Most storage devices that use on-the-fly compression do not take into consideration the type of data that is being compressed or any other relevant knowledge. In this embodiment, the storage device utilizes knowledge of the data being transferred to/from it or data that is already stored to perform selective on-the-fly data compression. 
     Exemplary Host and Storage Devices 
     Turning now to the drawings,  FIG. 1  is a block diagram of a host device (computing platform/host)  50  and a storage device  100  of an embodiment. As shown in  FIG. 1 , the storage device  100  comprises a storage manager  105 , a storage memory controller  110 , and storage memory  120 . In one embodiment, the storage manager is software or firmware executed by the storage memory controller  110 . As shown by the arrows, I/O transactions are sent between the host device  50  and the storage device  100 . In general, a computing platform/host is a device that the storage device is in communication with. A computing platform typically includes some sort of hardware architecture and a software framework (including application frameworks). The combination allows software to run. Typical platforms include a computer&#39;s architecture, operating system, programming languages, and related user interface (e.g., run-time system libraries or graphical user interface). The “storage device” is a device that stores data from the computing platform/host device. 
       FIG. 2  is a more detailed block diagram of the host device  50  and the storage device  100  of an embodiment. As used herein, the phrase “in communication with” could mean directly in communication with or indirectly in communication with through one or more components, which may or may not be shown or described herein. For example, the host device  50  and storage device  100  can each have mating physical connectors that allow the storage device  100  to be removably connected to the host device  50 . The host device  50  can take any suitable form, such as, but not limited to, a mobile phone, a digital media player, a game device, a personal digital assistant (PDA), a personal computer (PC), a kiosk, a set-top box, a TV system, a book reader, or any combination thereof. In this embodiment, the storage device  100  is a mass storage device that can take any suitable form, such as, but not limited to, an embedded memory (e.g., a secure module embedded in the host device  50 ) and a handheld, removable memory card (e.g., a Secure Digital (SD) card, or a MultiMedia Card (MMC)), as well as a universal serial bus (USB) device and a removable or non-removable hard drive (e.g., magnetic disk or solid-state or hybrid drive). In one embodiment, the storage device  100  can take the form of an iNAND™ eSD/eMMC embedded flash drive by SanDisk Corporation. 
     As shown in  FIG. 2 , the storage device  100  comprises a controller  110  and a memory  120 . The controller  110  comprises a memory interface  111  for interfacing with the memory  120  and a host interface  112  for interfacing with the host  50 . The controller  110  also comprises a central processing unit (CPU)  113 , a hardware crypto-engine  114  operative to provide encryption and/or decryption operations, read access memory (RAM)  115 , read only memory (ROM)  116  which can store firmware for the basic operations of the storage device  100 , and a non-volatile memory (NVM)  117  which can store a device-specific key used for encryption/decryption operations. In one embodiment, the storage manager  105  software/firmware is stored in the RAM  115 , ROM  116 , NVM  117 , or the memory  120  and is executed by the controller  110 . The controller  110  can be implemented in any suitable manner. For example, the controller  110  can take the form of a microprocessor or processor and a computer-readable medium that stores computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, an application specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, for example. Examples of controllers include, but are not limited to, the following microcontrollers ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. 
     The memory  120  can take any suitable form. In one embodiment, the memory  120  takes the form of a solid-state (e.g., flash) memory and can be one-time programmable, few-time programmable, or many-time programmable. However, other forms of memory, such as optical memory and magnetic memory, can be used. In this embodiment, the memory  120  comprises a public memory area  125  that is managed by a file system on the host  50  and a private memory area  136  that is internally managed by the controller  110 . The private memory area  136  can store a shadow master boot record (MBR) (as will be described below), as well as other data, including, but not limited to, content encryption keys (CEKs) and firmware (FW) code. However, access to the various elements in the private memory area  136  can vary. The public memory area  125  and the private memory area  136  can be different partitions of the same memory unit or can be different memory units. The private memory area  136  is “private” (or “hidden”) because it is internally managed by the controller  110  (and not by the host&#39;s controller  160 ). 
     Turning now to the host  50 , the host  50  comprises a controller  160  that has a storage device interface  161  for interfacing with the storage device  100 . The controller  160  also comprises a central processing unit (CPU)  163 , an optional crypto-engine  164  operative to provide encryption and/or decryption operations, read access memory (RAM)  165 , read only memory (ROM)  166 , a security module  171 , and storage  172 . The storage device  100  and the host  150  communicate with each other via a storage device interface  161  and a host interface  112 . For operations that involve the secure transfer of data, it is preferred that the crypto-engines  114 ,  164  in the storage device  100  and host  150  be used to mutually authenticate each other and provide a key exchange. After mutual authentication is complete, it is preferred that a session key be used to establish a secure channel for communication between the storage device  150  and host  100 . Alternatively, crypto-functionality may not be present on the host side, where authentication is done only using a password. In this case, the user types his password into the host device  50 , and the host device  50  sends it to the storage device  100 , which allow access to the public memory area  125 . The host  50  can contain other components (e.g., a display device, a speaker, a headphone jack, a video output connection, etc.), which are not shown in  FIG. 2  to simplify the drawings. 
     Embodiments Relating to a Storage Device being Aware of I/O Transactions and Stored Data 
     As mentioned above, data in many of today&#39;s storage devices is typically written to/read from the storage device according to and based on commands that are received from the host device, regardless of the characteristics and meaning of the information being stored. Also, no predefined knowledge of the system is accounted for. This embodiment is generally directed to the use of data being transferred to/from the storage device, as well as the way this data is being transferred (e.g. protocol, pattern) to add knowledge to the storage manager of the storage device to optimize and utilize its work. This can be accomplished with or without support or handshake or other information coming from the host device. In other words, this embodiment proposes a way for handling host requests for data (e.g., read and write requests) based on the characteristics of the host-requested data, characteristics of other data already residing on the storage device, or any predefined knowledge in a manner that is transparent to the host device. In general, these embodiments use predefined file system (FS) knowledge to optimize the storage device&#39;s operation. This is sometimes referred to herein as “file system awareness.” This embodiment will now be described in more detail below. 
     First, as an optional step, the storage device  100  can internally access data for determining the logical partition layout of the storage device  100 . For example, the storage device  100  can probe the boot record to identify the logical partitions layout of the storage device. Alternatively, other methods can be used to determine the logical partition layout of the storage device. The boot record can be stored in a boot block or sector, which is a region of the storage device  100  that contains machine code intended to be executed by built-in firmware. This region has a size and location (perhaps corresponding to a single logical disk sector in the CHS addressing scheme or like a globally unique identifier (GUID) partition table) specified by the design of the computing platform. The usual purpose of a boot sector is to boot a program (usually, but not necessarily, an operating system) stored on the same storage device. As used herein, a “block” is a unit of storage space that the storage device can manage, read, and write. 
     Next, the file system type of each logical partition is identified. This can be done, for example, based on information stored in the logical partition layout. For each file system, the storage device  100  can analyze the file system tables and data structures to identify information to the storage manager (e.g., metadata, “hot spot blocks,” special locations in the memory, and/or special data patterns and upcoming operations). A few examples of such information may include, but is not limited to: data that is being used as temporary data; data designated to be stored as backup; data stored as a virtual memory or as a swap file or in a swap disk; information, such as metadata and its location in the file system (e.g., file allocation tables in a FAT file system include sensitive metadata information that is located at the beginning of the logical partition associated with the file system); and non-active storage areas in the memory that (in high probability) will not be used (e.g., areas located between two logical partitions and not covered by any of them). 
     Based on this obtained information, the storage manager of the storage device controller can optimize host request handling (such as: read, write, erase or other accesses involving or not involving data). For example, the storage device controller can identify frequently used storage areas (e.g., most accessed or most likely to be accessed storage areas, such as a FAT table) and handle them accordingly. As another example, the storage device controller can identify “volatile in behavior” data (e.g., data which might be “lost” without compromising the integrity of the system), which may involve caching the volatile data without actually storing it in the internal non-volatile memory of the storage device, or storing this data in memory areas that lack power failure immunity. As yet another example, the storage device controller can use the identified not active storage areas for extending the memory management capabilities. Additionally, the storage device controller can perform selective data compression on, for example, data that is identified as being less sensitive to performance such as backup data, data that may have high compression efficiency, and data that is rarely accessed. Selective data compression will be described in more detail below. 
     There are several advantages associated with this embodiment. For example, this embodiment can enable a storage manager within a storage device to alter its behavior based on knowledge driven by the data stored on it, how this data is stored and accessed (e.g., write/read patterns), and prior system knowledge. Such different behaviors can enable the storage device to optimize its operation, as well as achieve higher reliability. All this can be achieved in a manner which is transparent to the host device. 
     Returning to the drawings,  FIGS. 3-9  are flow charts that illustrate the above steps in more detail.  FIG. 3  shows an overview of the detection process, with the storage device  100  first detecting and analyzing usages of stored physical partitions (act  300 ) and then detecting and analyzing usages of stored logical partitions (act  310 ).  FIG. 4  shows a process of detecting and analyzing usages of stored physical partitions in more detail, using, as an example, an embedded multimedia card (eMMC) version 4.3 or higher device. First, it is determined whether the storage device  100  is eMMC version 4.3 or higher (act  410 ). If it is not, the detection process continues (act  415 ). If it is, an index is set to one (act  420 ), and it is determined if the index is less than or equal to the number of physical boot partitions (act  425 ). If the index is less than or equal to the number of physical boot partitions, it is then determined if the boot partition at that index is being used for booting (act  430 ). If the boot partition at that index is being used for booting, the boot partition data is optimized to improve performance (act  435 ). If the boot partition at that index is not being used for booting, it is determined if the boot partition at that index is used at all (act  440 ). If the boot partition at that index is used, any un-utilized storage space is utilized for storage device internal needs (act  445 ). Otherwise, the index is increased (act  450 ), and act  425  is performed again, where it is determined if the index is less than or equal to the number of physical boot partitions. 
     If the index is greater than the number of physical boot partitions, it is determined if a replay protected memory block (RPMB) partition is being used for boot (act  455 ). If it is, the RPMB partition data is optimized to improve performance (act  460 ). If it is not, it is determined if the RPMB partition is being used at all (act  465 ). If it is not, the detection process continues (act  415 ). If it is being used, un-used storage space is utilized for storage device internal needs (act  470 ). 
     Returning to  FIG. 3 , the next step is to detect and analyze usages of storage logical partitions (act  310 ). This is shown in more detail in  FIG. 5 . As shown in  FIG. 5 , the first step in this process is to identify the storage logical partition layouts (act  505 ), and this act is shown in more detail in  FIG. 6 . First, it is determined if the logical partition disk layout is known (act  605 ). If it is, the detection process continues (act  610 ). If it is not, LBA  0  is read (act  615 ), and bytes  510  and  511  are analyzed to determine if they contain certain data (0x55 and 0xAA, respectively), as this indicates a valid MBR signature (act  620 ). If there isn&#39;t a valid MBR signature, the detection process continues (act  610 ). However, if there is a valid MBR signature, byte  450  is analyzed to see if it contains 0xEE (act  625 ). If byte  450  does not contain that data, the MBR is an MSDOS MBR, which is then parsed (act  630 ) before the detection process continues (act  610 ). Otherwise, the partition is a UEFI system partition GUID, which is then parsed (act  635 ) before the detection process continues (act  610 ). 
       FIG. 7  provides more detail on how to parse the UEFI system partition GUID (act  635 ). First, 16 bytes are read from LBA  0  offset  446 , which is the first protective MBR partition record (act  700 ). Then, the variable gptLba is set to the staring LBA (act  710 ). The LBA at this variable is then read to determine if there is a GUID partition table (GPT) header (act  715 ). If the header is not found, the detection process continues (act  725 ). However, if the header is found, various variables are set (acts  730 - 750 ), and a loop is performed (acts  750 - 766 ), resulting in internally storing any relevant information from a partition entry (e.g., start LBA, end LBA, OS type, areas that are expected to be unused, or areas that are good candidates to be compressed) (act  770 ). 
     Returning to  FIG. 5 , if such “vital” information is found (act  510 ), the information related to the logical partition disk layout is internally stored (act  515 ), and a runtime awareness mechanism is run (act  520 ) to determine if at least one logical partition is detected (act  525 ). If at least one logical partition is not detected, the detection process ends (act  530 ). Otherwise, a loop is entered to cycle through the number of logical partitions that were found (acts  525 - 585 ). As part of this process, a given logical partition is parsed (act  555 ), and this act is shown in more detail in  FIG. 8 . As shown in  FIG. 8 , part of this process is to determine if various file systems are used and then to parse the vital information from such systems (acts  800 - 840 ). An example of this process for one file system (FAT32) will be illustrated, as the processes for the other file systems can be understood to be similar to this example, with the necessarily adjustments made due to the particulars of the given file system. Parsing a FAT32 file system for vital information is shown in more detail in  FIG. 9 . As shown in  FIG. 9 , LBA  0  is read from the logical boot partition (act  905 ) and various fields are analyzed in order to parse the file system (acts  910 - 955 ). The end of this process is that detection is continued (act  915 ). 
     As mentioned above, the information learned from the detection mechanisms described in these figures can be used to optimize host requests handling (such as: read, write, erase or other accesses involving or not involving data). This can enable a storage manager in a storage device to alter its behavior based on knowledge driven by the data stored on it, how this data is stored and accessed (e.g., write/read patterns), and prior system knowledge. This allows the storage device to optimize its operation, as well as achieve higher reliability, without involved the host device. 
     Embodiments Relating to Utilizing Un-Used Storage Space for Storage Device Internal Needs 
     Storage devices today may contain storage space which, in high probability, will not be used during the lifetime of the storage device. Despite the fact that this storage space is not being used, this area in the memory is not exploited for other purposes by the storage device. An example for such unused storage space is LBAs (Logical Blocks) that reside in between two logical partitions, one not starting immediately after the previous one ends. Thus, today&#39;s storage devices do not use any pre-defined knowledge about the data stored in the storage device to optimize the storage management by better exploiting un-used user space. For example, in the situation described above, the unused LBA addresses between logical partitions are never accessed by the host. 
     In this embodiment, the storage device uses already-retrieved knowledge on data being transferred to/from it as well as the way this data is being transferred (e.g. protocol, pattern, etc.) to identify non-active storage areas in the memory that, in high probability, will not be used. This provides the storage device  100  with the ability to better exploit unused user storage areas in the memory, which may optimize storage behavior and improve reliability and performance of the device. 
     In this embodiment, the storage device  100  can first identify unused user storage space based on internal knowledge, such as the determining the logical partition layout, as discussed in the previous embodiment. Examples of such unused storage areas include, but are not limited to, storage areas located between two logical partitions (not covered by any of them) and a storage area with distinct purposes (e.g., both eMMC boot partitions if they are not used by the host device and an eMMC RPMB partition). 
     The storage device  100  can then perform risk analysis on the identified storage areas to determine characteristics of the identified storage areas. These “area characteristics” can include, but are not limited to, an area size and LBA range that should stand to the minimum internal requirements, the type of memory area (e.g., normal/fast areas, technology (x Bit per Cell)), area location significance (e.g. an area located between two logical partition as described above should be fairly safe to use), areas where usage is well defined (e.g., boot and RPMB partitions in eMMC 4.3 onwards storage devices), area access frequency (e.g., detecting how often, if at all, a proposed area was accessed by the host device), and area data content (e.g., an area contained erased data or obsolete data). The storage device  100  can also perform risk analysis to determine if a rule would be violated. The storage device  100  can identify a set of rules that, when violated, disable the storage manager&#39;s internal usage of the selected area. This can happen, for example, when a storage disk layout would be modified or when accessing or modifying an area in between two logical partitions. 
     Based on the risk analysis, the use of a selected area can be altered so as to be used and managed as required by the storage manager of the storage device  100  for performing a variety of internal operations, without the host device&#39;s knowledge. Such operations may include, but are not limited to, improving the storage manager&#39;s I/O transactions handling, self-maintenance and housekeeping, and improved power failure immunity, reliability and performance. 
     In case a selected area contains valid data (e.g., data that was not erased), the storage manager can operate to maintain the integrity of the data, which may include compressing the data to utilize at least part of the range, as will be described in more detail in the next section. Also, in one embodiment, the total exported capacity reported to the host device remains unchanged (i.e., as if the unused storage space was not identified and reused), maintaining the original storage capacity. 
     The storage device  100  can also monitor I/O transactions to and from the selected areas that may affect (e.g., abort) the previous ruling with respect to the identified un-used areas. If such a transaction is detected, the storage manager can stop using the selected area(s) for its internal use in a manner transparent to the host device. This can occur, for example, when the host device attempts to reformat the location of a logical partition. 
     Returning to the drawings,  FIGS. 10-13  are flow charts of various processes performed in one particular implementation of the embodiment discussed above. It should be noted that this is merely an example, and other processes can be performed. Starting with  FIG. 10 , first, the storage device  100  identifies unused user storage space based on internal knowledge (act  1000 ). This act can be performed as described above in the previous section. Next, a loop is performed to perform risk analysis and rule violation analysis on various areas (acts  1010 - 1050 ). Two examples of the risk analysis act (act  1025 ) are performing a boot partition risk analysis and performing a GPT area risk analysis. These analyses are shown in more detail in  FIGS. 11 and 12 , respectively. 
       FIG. 11  relates to the risk analysis of a boot partition. As shown in  FIG. 11 , the storage device  100  first determines if a partition was ever accessed (act  1105 ). If the partition was accessed, it is then determined if the partition was accessed at least once (acts  1100 ,  1115 , and  1120 ). Otherwise, the storage device  100  determines if the unused storage space passes minimum criteria (act  1125 ), and either internally stores the risk analysis results (act  1130 ) or ends the risk analysis (act  1135 ).  FIG. 12  shows the various acts (acts  1200 - 1250 ) that can be performed to perform risk analysis of the GPT area. 
     Returning to  FIG. 10 , act  1045  relates to determining if there would be a violation of a rule, and  FIG. 13  provides more detail on one possible implementation of that act. As shown in  FIG. 13 , an I/O transaction is probed (act  1300 ). A test is then applied (act  1310 ). Based on the results of the test (act  1320 ), either a determination of risk breaking rules is performed (acts  1330 - 1350 ) or the I/O transaction is continued (act  1360 ). 
     Embodiments Relating to Selective Data Compression 
     Most storage devices that use on-the-fly compression do not take into consideration the type of data that is being compressed or any other relevant knowledge relating to data already stored in the storage device, nor do they take into consideration any pre-defined knowledge about the data to be compressed and/or any previous-related transactions to and from the storage device which may affect the way and the efficiency of the compression that is being performed. In this embodiment, the storage device  100  utilizes already-retrieved knowledge on data being transferred to/from it or data that is already stored to perform selective on-the-fly data compression and background maintenances compression by the storage manager. This enables the storage device to alter its behavior based on knowledge driven by the data stored on it, how this data is stored and accessed (e.g. write/read patterns), and prior system knowledge. Such different behaviors can provide the ability to compress only data which has high compression efficiency while preventing compressing data having a low compression efficiency, thereby optimizing overall system performance. 
     In one embodiment, the storage device  100  first identifies specific data storage space based on internal knowledge, such as the logical partition layout, as described above. Examples of data that may be suitable for compression include, but are not limited to, data that is identified as being less sensitive to performance such as backup data, data that has a relatively-high compression efficiency (e.g., texts files), and data that is rarely accessed. Examples of data that may be less ideal for compression include, but are not limited to, data that is frequently rewritten and reread and if compressed, may result in reduced performance (e.g., FAT tables of FAT32 file system), as well as data that has relatively-low compression efficiency (e.g., jpeg file images). 
     Next, the storage device  100  performs risk and compression analysis on the identified storage areas or data transaction. This analysis can involve determining what compression algorithm to use based on one or more of the following: potential compression on the data, access and modification frequency of the data, and performance impacts, such as duration of the compression algorithm; uncompressing and reading the compressed data; and modifying already-compressed data. The analysis can also involved compression scheduling (e.g., should the compression occur on-the-fly, as an internal background operation or any other storage manager idle time), as well as determining whether a rule, if violate, should disable the compression process (e.g., reformatting a logical partition and changes in the data is frequently being accessed and/or modified. 
     Based on the risk and compression analysis, the storage device  100  can select storage areas or data transactions that will be managed as needed by the storage manager for performing a variety of internal operations, transparently to the host device. Such operations can include, but are not limited to, reducing the duration of internal memory write operation, reducing the actual memory space used to store user data and increase available memory space the storage manager internal work, improving the internal memory mapping mechanism, and reducing write amplification to improve overall product life cycle. 
     In one embodiment, the total user space reported to the host device will at least remain unchanged to the original storage capacity, so that the storage management described herein is transparent to the host device. For example, 100 MB of data which is compressed to 20 MB will still appear as 100 MB of data. It may also be desired to include an internal mechanism that will monitor I/O transactions to the storage device  100  to identify any violation of a rule on the selected area(s) and data being compressed. If such a transaction is monitored, the storage manager of the storage device  100  can stop the compression method on the selected area(s) or data, transparently to the host device. Such a situation can occur, for example, when reformatting the location of the logical partition. 
     Returning to the drawings,  FIGS. 14-17  are flow charts of various processes performed in one particular implementation of the embodiment discussed above. It should be noted that this is merely an example, and other processes can be performed. Starting with  FIG. 14 , first, the storage device  100  identifies unused user storage space based on internal knowledge (act  1400 ). This act can be performed as described above in the previous section. Next, a loop is performed to detect the success for selective data compression on a candidate (acts  1410 - 1460 ).  FIG. 15  (acts  1500 - 1540 ) provides more detail on the detecting act (act  1430 ). This example contemplates that there can be two types of candidates: static (e.g., an address range) and dynamic (e.g., a file). Detecting the success probability of static selective data compression on a candidate is shown in acts  1600 - 1630  in  FIG. 16 , while detecting the success probability of dynamic selective data compression on a candidate is shown in acts  1700 - 1735  in  FIG. 17 . 
     CONCLUSION 
     It is intended that the foregoing detailed description be understood as an illustration of selected forms that the invention can take and not as a definition of the invention. It is only the following claims, including all equivalents, that are intended to define the scope of the claimed invention. Finally, it should be noted that any aspect of any of the preferred embodiments described herein can be used alone or in combination with one another.