Patent Grant
9021295
The present invention generally relates to a disk drive system and method, and more particularly to a disk drive system having capabilities such as dynamic data allocation and disk drive virtualization, etc.
The existing disk drive systems have been designed in such a way that a virtual volume data storage space is statically associated with physical disks with specific size and location for storing data. These disk drive systems need to know and monitor/control the exact location and size of the virtual volume of data storage space in order to store data. In addition, the systems often need bigger data storage space whereby more RAID devices are added. However, often times these additional RAID devices are expensive and not required until extra data storage space is actually needed.
Therefore, there is a need for an improved disk drive system and method. There is a further need for an efficient, dynamic data allocation and disk drive space and time management system and method.
The present invention provides an improved disk drive system and method capable of dynamically allocating data. The disk drive system may include a RAID subsystem having a matrix of disk storage blocks and a disk manager having at least one disk storage system controller. The RAID subsystem and disk manager dynamically allocate data across the matrix of disk storage blocks and a plurality of disk drives based on RAID-to-disk mapping. The RAID subsystem and disk manager determine whether additional disk drives are required, and a notification is sent if the additional disk drives are required. Dynamic data allocation allows a user to acquire a disk drive later in time when it is needed. Dynamic data allocation also allows efficient data storage of snapshots/point-in-time copies of virtual volume matrix or pool of disk storage blocks, instant data replay and data instant fusion for data backup, recovery etc., remote data storage, and data progression, etc. Data progression also allows deferral of a cheaper disk drive since it is purchased later in time.
In one embodiment, a matrix or pool of virtual volumes or disk storage blocks is provided to associate with physical disks. The matrix or pool of virtual volumes or disk storage blocks is monitored/controlled dynamically by the plurality of disk storage system controllers. In one embodiment, the size of each virtual volume can be default or predefined by a user, and the location of each virtual volume is default as null. The virtual volume is null until data is allocated. The data can be allocated in any grid of the matrix or pool (e.g. a “dot” in the grid once data is allocated in the grid). Once the data is deleted, the virtual volume is again available as indicated to be “null”. Thus, extra data storage space and sometimes expensive data storage devices, e.g. RAID devices, can be acquired later in time on a need basis.
In one embodiment, a disk manager may manage a plurality of disk storage system controllers, and a plurality of redundant disk storage system controllers can be implemented to cover the failure of an operated disk storage system controller.
In one embodiment, a RAID subsystem includes a combination of at least one of RAID types, such as RAID-0, RAID-1, RAID-5, and RAID-10. It will be appreciated that other RAID types can be used in alternative RAID subsystems, such as RAID-3, RAID-4, RAID-6, and RAID-7, etc.
The present invention also provides a dynamic data allocation method which includes the steps of: providing a default size of a logical block or disk storage block such that disk space of a RAID subsystem forms a matrix of disk storage blocks; writing data and allocating the data in the matrix of the disk storage blocks; determining occupancy rate of the disk space of the RAID subsystem based on historical occupancy rate of the disk space of the RAID subsystem; determining whether additional disk drives are required; and sending a notification to the RAID subsystem if the additional disk drives are required. In one embodiment, the notification is sent via an email.
One of the advantages of the disk drive system of the present invention is that the RAID subsystem is capable of employing RAID techniques across a virtual number of disks. The remaining storage space is freely available. Through monitoring storage space and determining occupancy rate of the storage space of the RAID subsystem, a user does not have to acquire a large sum of drives that are expensive but has no use at the time of purchase. Thus, adding drives when they are actually needed to satisfy the increasing demand of the storage space would significantly reduce the overall cost of the disk drives. Meanwhile, the efficiency of the use of the drives is substantially improved.
Another advantage of the present invention is that the disk storage system controller is universal to any computer file system, not just to a specific computer file system.
The present invention also provides a method of data instant replay. In one embodiment, the data instant replay method includes the steps of: providing a default size of a logical block or disk storage block such that disk space of a RAID subsystem forms a page pool of storage or a matrix of disk storage blocks; automatically generating a snapshot of volumes of the page pool of storage or a snapshot of the matrix of disk storage blocks at predetermined time intervals; and storing an address index of the snapshot or delta in the page pool of storage or the matrix of the disk storage blocks such that the snapshot or delta of the matrix of the disk storage blocks can be instantly located via the stored address index.
The data instant replay method automatically generates snapshots of the RAID subsystem at user defined time intervals, user configured dynamic time stamps, for example, every few minutes or hours, etc., or time directed by the server. In case of a system failure or virus attack, these time-stamped virtual snapshots allow data instant replay and data instant recovery in a matter of a few minutes or hours, etc. The technique is also referred to as instant replay fusion, i.e. the data shortly before the crash or attack is fused in time, and the snapshots stored before the crash or attack can be instantly used for future operation.
In one embodiment, the snapshots can be stored at a local RAID subsystem or at a remote RAID subsystem so that if a major system crash occurs due to, for example a terrorist attack, the integrity of the data is not affected, and the data can be instantly recovered.
Another advantage of the data instant replay method is that the snapshots can be used for testing while the system remains its operation. Live data can be used for real-time testing.
The present invention also provides a system of data instant replay including a RAID subsystem and a disk manager having at least one disk storage system controller. In one embodiment, the RAID subsystem and disk manager dynamically allocate data across disk space of a plurality of drives based on RAID-to-disk mapping, wherein the disk space of the RAID subsystem forms a matrix of disk storage blocks. The disk storage system controller automatically generates a snapshot of the matrix of disk storage blocks at predetermined time intervals and stores an address index of the snapshot or delta in the matrix of the disk storage blocks such that the snapshot or delta of the matrix of the disk storage blocks can be instantly located via the stored address index.
In one embodiment, the disk storage system controller monitors frequency of data use from the snapshots of the matrix of the disk storage blocks and applies an aging rule such that the less frequently used or accessed data is moved to the less expensive RAID subsystem. Similarly, when the data in the less expensive RAID subsystem starts to be used more frequently, the controller moves the data to the more expensive RAID subsystem. Accordingly, a user is able to choose a desired RAID subsystem portfolio to meet its own storage needs. Therefore, the cost of the disk drive system can be significantly reduced and dynamically controlled by a user.
These and other features and advantages of the present invention will become apparent to those skilled in the art from the following detailed description, wherein it is shown and described illustrative embodiments of the invention, including best modes contemplated for carrying out the invention. As it will be realized, the invention is capable of modifications in various obvious aspects, all without departing from the spirit and scope of the present invention. Accordingly, the drawings and detailed description are to be regarded as illustrative in nature and not restrictive.
The present invention provides an improved disk drive system and method capable of dynamically allocating data. The disk drive system may include a RAID subsystem having a page pool of storage that maintains a free list of RAIDs or alternatively, a matrix of disk storage blocks, and a disk manager having at least one disk storage system controller. The RAID subsystem and disk manager dynamically allocate data across the page pool of storage or the matrix of disk storage blocks and a plurality of disk drives based on RAID-to-disk mapping. The RAID subsystem and disk manager determine whether additional disk drives are required, and a notification is sent if the additional disk drives are required. Dynamic data allocation allows a user to acquire a disk drive later in time when it is needed. Dynamic data allocation also allows efficient data storage of snapshots/point-in-time copies of virtual volume matrix or pool of disk storage blocks, instant data replay and data instant fusion for data backup, recovery etc., remote data storage, and data progression, etc. Data progression also allows deferral of a cheaper disk drive since it is purchased later in time.
The disk drive system 100 having a dynamic data allocation (or referred to “disk drive virtualization”) in accordance with the principles of the present invention is illustrated in
Another embodiment of dynamic data allocation of the present invention is shown in
Accordingly, the RAID subsystem is capable of employing RAID techniques across a virtual number of disks. The remaining storage space is freely available. Through monitoring storage space and determining occupancy rate of the storage space of the RAID subsystem, a user does not have to acquire a large sum of drives that are expensive but has no use at the time of purchase. Thus, adding drives when they are actually needed to satisfy the increasing demand of the storage space would significantly reduce the overall cost of the disk drives. Meanwhile, the efficiency of the use of the drives is substantially improved.
Also, dynamic data allocation of the disk drive system of the present invention allows efficient data storage of snapshots/point-in-time copies of virtual volume page pool of storage or virtual volume matrix of disk storage blocks, instant data replay and data instant fusion for data recovery and remote data storage, and data progression.
The above features and advantages resulted from a dynamic data allocation system and method and the implementation thereof in the disk drive system 100 are discussed below in details:
In one embodiment, dynamic data allocation, sometimes referred to as “virtualization” or “disk space virtualization”, efficiently handles a large number of read and write requests per second. The architecture may require the interrupt handlers to call a cache subsystem directly. Dynamic data allocation may not optimize requests as it does not queue them, but it may have a large number of pending requests at a time.
Dynamic data allocation may also maintain data integrity and protect the contents of the data for any controller failure. To do so, dynamic data allocation writes state information to RAID device for reliable storage.
Dynamic data allocation may further maintain the order of read and write requests and complete read or write requests in the exact order that the requests were received. Dynamic data allocation provides for maximum system availability and supports remote replication of data to a different geographical location.
In addition, dynamic data allocation provides recovery capabilities from data corruption. Through snapshot, a user may view the state of a disk in the past.
Dynamic data allocation manages RAID devices and provides a storage abstraction to create and expand large devices.
Dynamic data allocation presents a virtual disk device to the servers; the device is called a volume. To the server, the volume acts the same. It may return different information for serial number, but the volumes behave essentially like a disk drive. A volume provides a storage abstraction of multiple RAID devices to create a larger dynamic volume device. A volume includes multiple RAID devices, allowing for the efficient use of disk space.
Dynamic data allocation maintains data integrity of the volumes. Data is written to the volumes and confirmed to the server. Data integrity covers various controller configurations including stand alone and redundant through a controller failure. Controller failure includes power failure, power cycle, software exception, and hard reset. Dynamic data allocation generally does not handle disk drive failures which are covered by RAID.
Dynamic data allocation provides the highest levels of data abstraction for the controller. It accepts requests from the front end and ultimately uses RAID devices to write the data to disks.
Dynamic data allocation includes a number of internal subsystems:
Dynamic data allocation also logs any errors and significant changes in configuration.
Depending on volume configuration, dynamic data allocation passes a request to a number of external layers. Remote replication passes requests to the front end, destined for a remote destination volume. The RAID Interface passes requests to RAID. Copy/mirror/swap passes requests back to dynamic data allocation to a destination volume.
Dynamic data allocation subsystems that affect data integrity may require support for controller coherency. As shown in
In one operation, the disk storage system 1400 automatically generates a snapshot of the matrix of disk storage blocks or virtual volumes 1404 at predetermined time intervals and stores an address index of the snapshot or delta in the matrix of the disk storage blocks or virtual volumes 1404 such that the snapshot or delta of the matrix of the disk storage blocks or virtual volumes 1404 can be instantly located via the stored address index.
Further in one operation, the disk storage system controller 1402 monitors frequency of data use from the snapshots of the matrix of the disk storage blocks 1404 and applies an aging rule such that the less frequently used or accessed data is moved to the less expensive RAID subsystem. Similarly, when the data in the less expensive RAID subsystem starts to be used more frequently, the controller moves the data to the more expensive RAID subsystem. Accordingly, a user is able to choose a desired RAID subsystem portfolio to meet its own storage needs. Therefore, the cost of the disk drive system can be significantly reduced and dynamically controlled by a user.
A RAID subsystem and disk manager dynamically allocate data across disk space of a plurality of disk drives based on RAID-to-disk mapping. In one embodiment, the RAID subsystem and disk manager determine whether additional disk drives are required, and a notification is sent if the additional disk drive is required.
The disk manager 106, as shown in
In one embodiment of the present invention, the disk manager 106 is at least three-fold: abstraction, configuration, and I/O optimization. The disk manager 106 presents “disks” to upper layers which could be, for example, locally or remotely attached physical disk drives, or remotely attached disk systems.
The common underlying characteristic is that any of these devices could be the target of I/O operations. The abstraction service provides a uniform data path interface for the upper layers, particularly the RAID subsystem, and provides a generic mechanism for the administrator to manage target devices.
The disk manager 106 of the present invention also provides disk grouping capabilities to simplify administration and configuration. Disks can be named, and placed into groups, which can also be named. Grouping is a powerful feature which simplifies tasks such as migrating volumes from one group of disks to another, dedicating a group of disks to a particular function, specifying a group of disks as spares, etc.
The disk manager also interfaces with devices, such as a SCSI device subsystem which is responsible for detecting the presence of external devices. The SCSI device subsystem is capable, at least for fiber channel/SCSI type devices, of determining a subset of devices which are block-type target devices. It is these devices which are managed and abstracted by the disk manager.
Further, the disk manager is responsible for responding to flow control from a SCSI device layer. The disk manager has queuing capabilities, which presents the opportunity to aggregate I/O requests as a method to optimize the throughput of the disk drive system.
Furthermore, the disk manager of the present invention manages a plurality of disk storage system controllers. Also, a plurality of redundant disk storage system controllers can be implemented to cover the failure of an operated disk storage system controller. The redundant disk storage system controllers are also managed by the disk manager.
The disk manager interacts with several other subsystems. The RAID subsystem is the major client of the services provided by the disk manager for data path activities. The RAID subsystem uses the disk manager as the exclusive path to disks for I/O. The RAID system also listens for events from the disk manager to determine the presence and operational status of disks. The RAID subsystem also works with the disk manager to allocate extents for the construction of RAID devices. Management control listens for disk events to learn the existence of disks and to learn of operational status changes. In one embodiment of the present invention, the RAID subsystem 104 may include a combination of at least one of RAID types, such as RAID-0, RAID-1, RAID-5, and RAID-10. It will be appreciated that other RAID types can be used in alternative RAID subsystems, such as RAID-3, RAID-4, RAID-6, and RAID-7, etc.
In one embodiment of the present invention, the disk manager utilizes the services of configuration access to store persistent configuration and present transient read-only information such as statistics to the presentations layers. The disk manager registers handlers with configuration access for access to these parameters.
The disk manager also utilizes the services of the SCSI device layer to learn of the existence and operational status of block devices, and has an I/O path to these block devices. The disk manager queries the SCSI device subsystem about devices as a supporting method to uniquely identify disks.
The present invention also provides a method of data instant replay and data instant fusion.
As shown in
Accordingly, the data instant replay method automatically generates snapshots of the RAID subsystem at a user defined time intervals, user configured dynamic time stamps, for example, every few minutes or hours, etc., or time directed by the server. In case of a system failure or virus attack, these time-stamped virtual snapshots allow data instant replay and data instant recovery in a matter of a few minutes or hours, etc. The technique is also referred to as instant replay fusion, i.e. the data shortly before the crash or attack is fused in time, and the snapshots stored before the crash or attack can be instantly used for future operation.
The snapshots can be stored at a local RAID subsystem or at a remote RAID subsystem so that if a major system crash occurs due to, for example a terrorist attack, the integrity of the data is not affected, and the data can be instantly recovered.
Remote replication performs the service of replicating volume data to a remote system. It attempts to keep the local and remote volumes as closely synchronized as possible. In one embodiment, the data of the remote volume may not mirror a perfect copy of the data of the local volume. Network connectivity and performance may cause the remote volume to be out of synchronization with a local volume.
Another feature of the data instant replay and data instant fusion method is that the snapshots can be used for testing while the system remains its operation. Live data can be used for real-time testing.
An example of data instant replay is to utilize snapshots of disk storage blocks of a RAID subsystem in accordance with the principles of the present invention. Snapshot records write operations to a volume so that a view may be created to see the contents of a volume in the past. Snapshot thus also supports data recovery by creating views to a previous Point-in-Time Copy (PITC) of a volume.
The core of a snapshot implements create, coalesce, management, and I/O operations of the snapshot. Snapshot monitors writes to a volume and creates Point-in-Time Copies (PITC) for access through view volumes. It adds a Logical Block Address (LBA) remapping layer to a data path within the virtualization layer. This is another layer of virtual LBA mapping within the I/O path. The PITC may not copy all volume information, and it may merely modify a table that the remapping uses.
Snapshot tracks changes to volume data and provides the ability to view the volume data from a previous point-in-time. Snapshot performs this function by maintaining a list of delta writes for each PITC.
Snapshot provides multiple methods for PITC profiles including: application initiated, and time initiated. Snapshot provides the ability for the application to create PITC. The applications control the creation through the API on the server, which is delivered to the snapshot API. Also, snapshot provides the ability to create a time profile.
Snapshot may not implement a journaling system or recover all writes to a volume. Snapshot may only keep the last write to a single address within a PITC window. Snapshot allows a user to create PITC that covers a defined short period of time, such as minutes or hours, etc. To handle failures, snapshot writes all information to disk. Snapshot maintains volume data page pointers containing the delta writes. Since the tables provide the map to the volume data, and without it the volume data is inaccessible, the table information must handle controller failure cases.
View volume functions provide access to a PITC. View volume functions may attach to any PITC within the volume, except the active PITC. Attaching to a PITC is a relatively quick operation. Uses of view volume functions include testing, training, backup, and recovery. The view volume functions allow write operation and do not modify the underlying PITC it is based on.
In one embodiment, the snapshot is designed to optimize performance and ease use at the expense of disk space:
Snapshots add a LBA remapping layer to a volume. The remapping uses the I/O request LBA and the lookup table to convert the address to the data page. As shown in
A new volume, with snapshot enabled at the inception, only needs to include space for the new data pages. Snapshot does not create a list of pages to place in the bottom level PITC. The bottom level PITC is empty in this case. At allocation, all PITC pages are on the free list. By creating a volume with snapshot enabled at the inception, it may allocate less physical space than the volume presents. Snapshot tracks the writes to the volume. In one embodiment of the present invention, the NULL volume is not copied and/or stored in the page pool or matrix, thereby increasing the efficiency of the use of the storage space.
In one embodiment, for both allocation schemes, PITC places a virtual NULL volume at the bottom of the list. Reads to the NULL volume return blocks of zero. The NULL volume handles the sectors not previously written by the server. Writes to the NULL volume can not occur. The volume uses a NULL volume for reads to unwritten sectors.
The number of free pages depends on the size of the volume, the number of PITC, and the expected rate of data change. The system determines the number of pages to allocate for a given volume. The number of data pages may expand over time. Expansion may support a more rapid change in data than expected, more PITC, or a larger volume. New pages are added to the free list. The addition of pages to the free list may occur automatically.
Snapshot uses data pages to manage the volume space. Each data page may include megabytes of data Using the operating system tends to write a number of sectors in the same area of a volume. Memory requirements also dictate that snapshot uses pages to manage volumes. Maintaining a single 32-bit pointer for each sector of a one-terabyte volume may require eight gigabytes of RAM. Different volumes may have different page size.
Also, snapshot summarizes the data page pointers for the entire volume, at the time a PITC is taken to provide predictable read and write performance. Other solutions may require reads to examine multiple PITC to find the newest pointer. These solutions require table caching algorithm but has worst-case performance.
Snapshot summarizing in the present invention also reduces the worst-case memory usage of table. It may require that the entire table be loaded into memory, but it may require only a single table loaded.
The summary includes pages owned by the current PITC and may include pages from all previous PITC. To determine which pages the PITC may write, it tracks page ownership for each data page. It also tracks ownership for a coalesce process. To handle this, the data page pointer includes the page index.
1. Create table—Upon creation, table is created.
2. Commit to disk—This generates the storage on the disk for the PITC. By writing the table at this point, it guarantees that the required space to store the table information is allocated before the PITC is taken. At the same time, the PITC object is also committed to the disk.
3. Accept I/O—It has become the active PITC (AP)—It now handles reads and writes requests for the volume. This is the only state that accepts writes requests to the table. The PITC generates an event that it is now active.
4. Commit the Table to Disk—The PITC is no longer the AP, and no longer accepts additional pages. A new AP has taken over. After this point, the table will not change unless it is removed during a coalesce operation. It is read-only. At this point, the PITC generates an event that it is frozen and committed. Any service may listen to the event.
5. Release table memory—Frees the memory that the table required. This step also clears the log to state that all changes are written to disk.
The top-level PITC for a volume or a view volume is called the active PITC (AP). The AP satisfies all read and write requests to the volume. The AP is the only PITC for the volume that may accept write requests. The AP contains a summary of data page pointers for the entire volume.
The AP may be the destination, not the source, for a coalesce process. Being the destination, the AP increases the number of owned pages, but it does not change the view of the data.
For volume expansion, the AP immediately grows with the volume. The new pages point to the NULL volume. Non-AP PITC does not require modification for volume expansion.
Each PITC maintains a table to map an incoming LBA to a data page pointer to the underlying volume. The table includes pointers to data pages. The table needs to address more physical disk space than presented logical space.
The multi-level index contains a summary of the entire volume data page remapping. Each PITC contains a complete remapping list for the volume at the point-in-time it is committed.
The multi-level index structure uses different entry types for the levels of the table. The different entry types support the need to read the information from the disk, as well as store it in memory. The bottom level entries may only contain data page pointers. The top and middle level entries contain two arrays, one for the LBA of the next level table entry, and a memory pointer to the table.
As the presented volume size expands, the size of previous PITC tables does not need to increase, and the tables do not need to be modified. The information in the table may not change, since it is read only, and the expand process modifies the table by adding NULL page pointers to the end. Snapshot does not directly present the tables from previous PITC to the user.
An I/O operation asks the table to map an LBA to a data page pointer. The I/O then multiplies the data page pointer times the data page size to get the LBA of the underlying RAID. In one embodiment, data page size is a power of two.
The table provides an API to remap LBA, add page, and coalesce table.
Snapshot uses the data pages to store the PITC object and the LBA mapping tables. The tables directly access the RAID interface for I/O to its table entries. The table minimizes modification when reading and writing the table to the RAID device. Without modification, it becomes possible to read and write the table information directly into table entry structures. This reduces copies needed for I/O. Snapshot may use a change log to prevent the creation of hot-spots on the disk. A hot-spot is a location that is used repeatedly to track updates to the volume. The change log records updates to the PITC table, and the free list for the volume. During recovery, snapshot uses the change log to re-create the in-memory AP and free list.
Periodically, snapshot writes the PITC table and free list to disk, creating a checkpoint in the log and clearing it. This period may vary depending on the number of updates to the PITC. The coalesce process does not use the change log.
Snapshot data page I/O may require requests fit within the data page boundaries. If snapshot encounters an I/O request that spans the page boundaries it splits the request. It then passes the requests down to the request handlers. The write and read sections assume that an I/O fits within the page boundaries. The AP provides the LBA remapping to satisfy I/O requests.
The AP satisfies all write requests. Snapshot supports two different write sequences for owned and non-owned pages. The different sequence allow for the addition of pages to the table.
For the owned page sequence, the process includes the following:
1) Find the table mapping; and
2) Page Owned Write—Remap the LBA and write the data to the RAID interface.
A previously written page is the simple write request. Snapshot writes the data to the page, overwriting the current contents. Only data pages owned by the AP will be written. Pages owned by other PITC is read only.
For the non-owned page sequence, the process includes the following:
1) Find the table mapping;
2) Read previous Page—Perform a read to the data page such that the write request and the read data make up the complete page. This is the start of the copy on write process.
3) Combine the data—Put the data page read and the write request payloads into a single contiguous block.
4) Free List Allocate—Get a new data page pointer from the free list.
5) Write the combined data to the new data page.
6) Commit the new page information to the log.
7) Update the table—Change the LBA remapping in the table to reflect the new data page pointer. The data page is now owned by the PITC.
Adding a page may require blocking read and write requests until the page is added to the table. By writing the table updates to disk and keeping multiple cached copies of the log, snapshot achieves controller coherency.
With respect to read requests, the AP fulfills all read requests. Using the AP table the read request remaps the LBA to the LBA of the data page. It passes the remapped LBA to the RAID interface to satisfy the request. A volume may fulfill a read requests for a data page not previously written to the volume. These pages are marked with the NULL Address (All one's) in the PITC table. Requests to this address are satisfied by the NULL volume and return a constant data pattern. Pages owned by different PITC may satisfy a read request spanning page boundaries.
Snapshot uses a NULL volume to satisfy read requests to previously unwritten data pages. It returns all zeroes for each sector read. It does not have a RAID device or allocated space. It is anticipated that a block of all zeroes be kept in memory to satisfy the data requirements for a read to the NULL volume. All volumes share the NULL volume to satisfy read requests.
In one embodiment, a coalesce process removes a PITC and some of its owned pages from the volume. Removing the PITC creates more available space to track new differences. Coalescing compares two adjacent tables for differences and keeps only the newer differences. Coalescing occurs periodically or manually according to user configuration.
The process may include two PITC, the source and destination. The rules in one embodiment for eligible objects are as follows:
1) The source must be the previous PITC to the Destination—the source must be created before the destination.
2) A destination may not simultaneously be a source.
3) A source may not be referred to by multiple PITC. Multiple references occur when a view volume is created from a PITC.
4) The destination may support multiple references.
5) The AP may be a destination, but not a source.
The coalesce process writes all changes to disk and requires no coherency. If a controller fails, the volume recovers the PITC information from disk and resumes the coalesce process.
The process marks two PITC for coalescing and includes the following steps:
1) Source state set to coalesce source—the state is committed to disk for controller failure recovery. At his point source may no longer be accessed as its data pages may be invalid. The data pages may be returned to the free list, or ownership is transferred to destination.
2) Destination state set to coalesce destination—the state is committed to disk for controller failure recovery.
3) Load and compare tables—the process moves data page pointers. Freed data pages immediately are added to the free list.
4) Destination state set to normal—The process is complete.
5) Adjust the list—change the previous of the source next pointer to the destination. This effectively removes the source from the list.
6) Free the source—return any data pages used for control information to the free list.
The above process supports the combination of two PITC. It is appreciated to a person skilled in the art that coalesce can be designed to remove multiple PITC and create multiple sources in the single pass.
As shown in
The free list may maintain a trigger to automatically expand itself at a certain threshold. The trigger uses the page pool expansion method to add pages to the page pool. The automatic expansion could be a function of volume policy. More important data volume would be allowed to expand while less important volumes are forced to coalesce.
View volumes provide access to previous points-in-time and support normal volume I/O operations. A PITC tracks the difference between PITC, and the view volume allows the user to access the information contained within a PITC. A view volume branches from a PITC. View volumes support recovery, test, backup operations, etc. View volume creation occurs nearly instantaneously as it requires no data copies. The view volume may require its own AP to support writes to the view volume.
A view taken from the current state of the volume the AP may be copied from the current volume AP. Using the AP, the view volume allows write operations to the view volume without modifying the underlying data. The OS may require a file system or file rebuild to use the data. The view volume allocates space from the parent volume for the AP and written data pages. The view volume has no associated RAID device information. Deleting the view volume frees the space back to the parent volume.
The transition from the left of the figure (i.e. the initial state) to the middle of the figure shows the a write to pages 3 and 8. The write to page 3 requires a change to PITC I (AP). PITC I follows the new page write processing to add page 3 to the table. PITC reads unchanged information from page J and uses the drive page B to store the page. All future writes to page 3 in this PITC are handled without moving pages. The write to page 8 depicts the second case for writing to a page. Since PITC I already contains page 8, PITC I writes over that portion of the data in page 8. For this case, it exists on the drive page C.
The transition from the middle of the figure to the right of the figure (i.e. final state) shows the coalescing of PITC II and III. Snapshot coalescing involves removing older pages, respectively, while maintaining all the changes in both PITC. Both PITC contain pages 3 and 8. The process retains the newer pages from PITC II and frees the pages from PITC III, and it returns pages A and D to the free list.
Snapshot allocates data pages from the page pool to store free list and PITC table information. Control Page allocation sub-allocates the data pages to match the sizes needed by the objects.
A volume contains a page pointer for the top of the control page information. From this page all of the other information can be read.
Snapshot tracks the number of pages in-use at certain time intervals. This allows snapshot to predict when the user needs to add more physical disk space to the system to prevent snapshot from running out.
In one embodiment of the present invention, data progression (DP) is used to move data gradually to storage space of appropriate cost. The present invention allows a user to add drives when the drives are actually needed. This would significantly reduce the overall cost of the disk drives.
Data progression moves non-recently accessed data and historical snapshot data to less expensive storage. For non-recently accessed data, it gradually reduces the cost of storage for any page that has not been recently accessed. It may not move the data to the lowest cost storage immediately. For historical snapshot data, it moves the read-only pages to more efficient storage space, such as RAID 5, and to the least expensive storage if the page is no longer accessible by a volume.
The other advantages of the data progression of the present invention include maintaining fast I/O access to data currently being accessed, and reducing the need to purchase fast but expensive disk drives.
In operation, data progression determines the cost of storage using the cost of the physical media and the efficiency of RAID devices that are used for data protection. Data progression also determines the storage efficiency and moves the data accordingly. For example, data progression may convert RAID 10 to RAID 5 devices to more efficiently use the physical disk space.
Data progression defines accessible data as data that can be read or written by a server at the current time. It uses the accessibility to determine the class of storage a page should use. A page is read-only if it belongs to a historical PITC. If the server has not updated the page in the most recent PITC, the page is still accessible.
In
The following table illustrates various storage devices in an order of increasing efficiency or decreasing monetary expense. The list of storage devices may also follow a general order of slower write I/O access. Data progression computes efficiency of the logical protected space divided by the total physical space of a RAID device.
50%
80%
RAID 5 efficiency increases as the number of drives in the stripe increases. As the number of disks in a stripe increases, the fault domain increases. The increasing the numbers of drives in a stripe also increases the minimum number of disk necessary to create the RAID devices. In one embodiment, data progression does not use a RAID 5 stripe size larger than 9 drives due to the increase in the fault domain size and the limited efficiency increase. Data progression uses RAID 5 stripe sizes that are integer multiple of the snapshot page size. This allows data progression to perform full-stripe writes when moving pages to RAID 5 making the move more efficient. All RAID 5 configurations have the same write I/O characteristic for data progression purpose. For example, RAID 5 on an 2.5 inch FC disk may not effectively use the performance of those disks well. To prevent this combination, data progression needs to support the ability to prevent a RAID Type from running on certain disk types. The configuration of data progression can also prevent the system from using RAID 10 or RAID 5 space.
The types of disks are shown in the following table:
Data progression includes the ability to automatically classify disk drives that are relative to the drives within a system. The system examines a disk to determine its performance relative to the other disks in the system. The faster disks are classified in a higher value classification, and the slower disks are classified in a lower value classification. As disks are added to the system, the system automatically rebalances the value classifications of the disks. This approach handles both the systems that never change and the systems that change frequently as new disks are added. The automatic classification may place multiple drive types within the same value classification. If the drives are determined to be close enough in value, then they have the same value.
In one embodiment, a system contains the following drives:
With the addition of a 15K FC drive, Data progression automatically reclassifies the disks and demotes the 10K FC drive. This results in the following classifications:
In another embodiment, a system may have the following drive types:
Accordingly, the 15K FC drive is classified as the lower value classification, whereas the 15K FC drive is classified as the higher value classification.
If a SATA drive is added to the system, Data progression automatically reclassifies the disks. This results in the following classification:
Data progression may include waterfall progression. Typically, waterfall progression moves data to a less expensive resource only when the resource becomes totally used. The waterfall progression effectively maximizes the use of the most expensive system resources. It also minimizes the cost of the system. Adding cheap disks to the lowest pool creates a larger pool at the bottom.
The typical waterfall progression uses RAID 10 space and then a next of RAID space, such as RAID 5 space. This forces the waterfall to go directly to RAID 10 of the next class of disks. Alternatively, data progression may include mixed RAID waterfall progression as shown in
The mixed RAID waterfall also only moves pages to less expensive storage when the storage is limited. A threshold value, such as a percentage of the total disk space, limits the amount of storage of a certain RAID type. This maximizes the use of the most expensive storage in the system. When a storage approaches its limit, data progression automatically moves the pages to lower cost storage. Data progression may provide a buffer for write spikes.
It is appreciated that the above waterfall methods may move pages immediately to the lowest cost storage as in some cases, there may be a need in moving historical and non-accessible pages onto less expensive storage in a timely fashion. Historical pages may also be instantly moved to less expensive storage.
Data progression process determines if the page is accessible by any volume. The process checks PITC for each volume attached to a history to determine if the page is referenced. If the page is actively being used, the page may be eligible for promotion or a slow demotion. If the page is not accessible by any volume, it is moved to the lowest cost storage available. Data progression also factors in the time before a PITC expires. If snapshot schedules a PITC to expire shortly, no pages progress. If the page pool is operating in an aggressive mode, the pages may progress.
Data progression recent access detection needs to eliminate a burst of activity from promoting a page. Data progression separates read and write access tracking. This allows data progression to keep data on RAID 5 devices that are accessible. Operations like a virus scan or reporting only read the data. Data progression changes the qualifications of recent access when storage is running low. This allows data progression to more aggressively demote pages. It also helps fill the system from the bottom up when storage is running low.
Data progression may aggressively move data pages as system resources become low. More disks or a change in configuration are still necessary for all of these cases. Data progression lengthens the amount of time that the system may operate in a tight situation. Data progression attempts to keep the system operational as long as possible. The time is when all of its storage classes are out-of-space.
In the case where RAID 10 space is running low, and total available disk space is running low, data progression may cannibalize RAID 10 disk space to move to more efficient RAID 5. This increases the overall capacity of the system at the price of write performance. More disks are still necessary. If a particular storage class is completely used, data progression allows for borrowing on non-acceptable pages to keep the system running. For example, if a volume is configured to use RAID 10-FC for its accessible information, it may allocate pages from RAID 5-FC or RAID 10-SATA until more RAID10-FC space is available.
Data progression also supports compression to increase the perceived capacity of the system. Compression may only be used for historical pages that are not accessed, or as the storage of recovery information. Compression appears as another class of storage near the bottom of storage costs.
As shown in
In one embodiment, the device list may require the additional ability to track the cost of the storage class. The combination determines the class of the storage. This would occur if the user would like more or less granularity with the configured classes.
Compressed page may significantly impact CPU performance. For write access, a compressed page would require the entire page be decompressed and recompressed. Therefore, pages actively being accessed are not compressed, and returned to their non-compressed state. Writes may be necessary in conditions where storeage is extremely limited.
The PITC remap table points to the sub-allocation information and is marked to indicate the page that is compressed. Accessing a compressed page may require a higher I/O count than a non-compressed page. The access may require the reading of the sub-allocation information to retrieve the location of the actual data. The compressed data may be read from the disk and decompressed on the processor.
Data progression may require compression to be able to decompress parts of the entire page. This allows data progression read access to only decompress small portions of the page. The read-ahead feature of read cache may help with the delays of compression. A single decompression may handle a number of server I/O. Data progression marks pages that are not good candidates for compression so that it does not continually attempt to compress a page.
The PITC identifies candidates for movement and blocks I/O to accessible pages when they move. Data progression continually examines the PITC for candidates. The accessibility of pages continually changes due to server I/O, new snapshot page updates, and view volume creation/deletion. Data progression also continually checks volume configuration changes and summarize the current list of page classes and counts. This allows data progression to evaluate the summary and determine if there are possibly pages to be moved.
Each PITC presents a counter for the number of pages used for each class of storage. Data progression uses this information to identify a PITC that makes a good candidate to move pages when a threshold is reached.
RAID allocates a device from a set of disks based on the cost of the disks. RAID also provides an API to retrieve the efficiency of a device or potential device. It also needs to return information on the number of I/O required for a write operation. Data progression may also require a RAID NULL to use third-party RAID controllers as a part of data progression. RAID NULL may consume an entire disk and merely act as a pass through layer.
Disk manager may also automatically determine and store the disk classification. Automatically determining the disk classification may require changes to SCSI Initiator.
From the above description and drawings, it will be understood by those of ordinary skill in the art that the particular embodiments shown and described are for purposes of illustration only and are not intended to limit the scope of the present invention. Those of ordinary skill in the art will recognize that the present invention may be embodied in other specific forms without departing from its spirit or essential characteristics. References to details of particular embodiments are not intended to limit the scope of the invention.
This application is a continuation of U.S. patent application Ser. No. 10/918,329, filed on Aug. 13, 2004, which claims priority of U.S. Provisional Patent Application Ser. No. 60/495,204, filed Aug. 14, 2003; subject matter of which are incorporated herewith by reference.
| Number | Name | Date | Kind |
|---|---|---|---|
| 5155835 | Belsan | Oct 1992 | A |
| 5274807 | Hoshen et al. | Dec 1993 | A |
| 5276867 | Kenley et al. | Jan 1994 | A |
| 5327535 | Ogata et al. | Jul 1994 | A |
| 5331646 | Kreuger et al. | Jul 1994 | A |
| 5371882 | Ludlam | Dec 1994 | A |
| 5379412 | Eastridge et al. | Jan 1995 | A |
| 5390327 | Lubbers | Feb 1995 | A |
| 5392244 | Jacobson et al. | Feb 1995 | A |
| 5502836 | Hale et al. | Mar 1996 | A |
| 5548740 | Kiyohara | Aug 1996 | A |
| 5553285 | Krakauer et al. | Sep 1996 | A |
| 5572661 | Jacobson | Nov 1996 | A |
| 5613088 | Achiwa et al. | Mar 1997 | A |
| 5644701 | Takewaki | Jul 1997 | A |
| 5659704 | Burkes et al. | Aug 1997 | A |
| 5664187 | Burkes et al. | Sep 1997 | A |
| 5696934 | Jacobson et al. | Dec 1997 | A |
| 5742792 | Yanai et al. | Apr 1998 | A |
| 5784698 | Brady et al. | Jul 1998 | A |
| 5829053 | Smith et al. | Oct 1998 | A |
| 5835953 | Ohran | Nov 1998 | A |
| 5897661 | Baranovsky et al. | Apr 1999 | A |
| 5933834 | Aichelen | Aug 1999 | A |
| 5974515 | Bachmat et al. | Oct 1999 | A |
| RE36462 | Chang et al. | Dec 1999 | E |
| 6052759 | Stallmo et al. | Apr 2000 | A |
| 6052797 | Ofek et al. | Apr 2000 | A |
| 6058489 | Schultz et al. | May 2000 | A |
| 6070249 | Lee | May 2000 | A |
| 6073218 | DeKoning et al. | Jun 2000 | A |
| 6073221 | Beal et al. | Jun 2000 | A |
| 6073222 | Ohran | Jun 2000 | A |
| 6078932 | Haye et al. | Jun 2000 | A |
| 6085262 | Sawada | Jul 2000 | A |
| 6085298 | Ohran | Jul 2000 | A |
| RE36846 | Ng et al. | Aug 2000 | E |
| 6115781 | Howard | Sep 2000 | A |
| 6115788 | Thowe | Sep 2000 | A |
| 6131148 | West et al. | Oct 2000 | A |
| 6170037 | Blumenau | Jan 2001 | B1 |
| 6173361 | Taketa | Jan 2001 | B1 |
| 6192444 | White et al. | Feb 2001 | B1 |
| 6209059 | Ofer et al. | Mar 2001 | B1 |
| 6212531 | Blea et al. | Apr 2001 | B1 |
| 6215747 | Jobs | Apr 2001 | B1 |
| 6269431 | Dunham | Jul 2001 | B1 |
| 6269453 | Krantz | Jul 2001 | B1 |
| 6275897 | Bachmat | Aug 2001 | B1 |
| 6275898 | DeKoning | Aug 2001 | B1 |
| 6282671 | Islam et al. | Aug 2001 | B1 |
| 6311251 | Merritt et al. | Oct 2001 | B1 |
| 6341341 | Grummon et al. | Jan 2002 | B1 |
| 6347359 | Smith et al. | Feb 2002 | B1 |
| 6353878 | Dunham | Mar 2002 | B1 |
| 6356969 | DeKoning et al. | Mar 2002 | B1 |
| 6366987 | Tzelnic et al. | Apr 2002 | B1 |
| 6366988 | Skiba et al. | Apr 2002 | B1 |
| 6415296 | Challener et al. | Jul 2002 | B1 |
| 6434681 | Armangau | Aug 2002 | B1 |
| 6438638 | Jones et al. | Aug 2002 | B1 |
| 6457098 | DeKoning et al. | Sep 2002 | B1 |
| 6516425 | Belhadj et al. | Feb 2003 | B1 |
| 6560615 | Zayas et al. | May 2003 | B1 |
| 6584582 | O'Connor | Jun 2003 | B1 |
| 6591335 | Sade et al. | Jul 2003 | B1 |
| 6604171 | Sade | Aug 2003 | B1 |
| 6611897 | Komachiya et al. | Aug 2003 | B2 |
| 6618794 | Sicola et al. | Sep 2003 | B1 |
| 6631493 | Ottesen et al. | Oct 2003 | B2 |
| 6636778 | Basham et al. | Oct 2003 | B2 |
| 6718436 | Kim et al. | Apr 2004 | B2 |
| 6732125 | Autrey | May 2004 | B1 |
| 6799258 | Linde | Sep 2004 | B1 |
| 6804755 | Selkirk et al. | Oct 2004 | B2 |
| 6826711 | Moulton et al. | Nov 2004 | B2 |
| 6839827 | Beardsley et al. | Jan 2005 | B1 |
| 6839864 | Mambakkam et al. | Jan 2005 | B2 |
| 6857057 | Nelson et al. | Feb 2005 | B2 |
| 6857059 | Karpoff et al. | Feb 2005 | B2 |
| 6859882 | Fung | Feb 2005 | B2 |
| 6862609 | Merkey | Mar 2005 | B2 |
| 6871295 | Ulrich et al. | Mar 2005 | B2 |
| 6877109 | Delaney et al. | Apr 2005 | B2 |
| 6880059 | Mizuno et al. | Apr 2005 | B2 |
| 6883065 | Pittlekow et al. | Apr 2005 | B1 |
| 6904441 | Voigt | Jun 2005 | B2 |
| 6904599 | Cabrera et al. | Jun 2005 | B1 |
| 6907505 | Cochran et al. | Jun 2005 | B2 |
| 6912585 | Taylor et al. | Jun 2005 | B2 |
| 6915241 | Kohlmorgen et al. | Jul 2005 | B2 |
| 6915397 | Lubbers et al. | Jul 2005 | B2 |
| 6915454 | Moore et al. | Jul 2005 | B1 |
| 6938123 | Willis et al. | Aug 2005 | B2 |
| 6948038 | Berkowitz et al. | Sep 2005 | B2 |
| 6952794 | Lu | Oct 2005 | B2 |
| 6957294 | Saunders et al. | Oct 2005 | B1 |
| 6957362 | Armangau | Oct 2005 | B2 |
| 6981114 | Wu et al. | Dec 2005 | B1 |
| 6996582 | Daniels et al. | Feb 2006 | B2 |
| 6996741 | Pittlekow et al. | Feb 2006 | B1 |
| 7000069 | Bruning et al. | Feb 2006 | B2 |
| 7003567 | Suzuki et al. | Feb 2006 | B2 |
| 7003688 | Pittlekow et al. | Feb 2006 | B1 |
| 7017076 | Ohno et al. | Mar 2006 | B2 |
| 7032093 | Cameron | Apr 2006 | B1 |
| 7032119 | Fung | Apr 2006 | B2 |
| 7039778 | Yamasaki | May 2006 | B2 |
| 7043663 | Pittlekow et al. | May 2006 | B1 |
| 7047358 | Lee et al. | May 2006 | B2 |
| 7051182 | Blumenau et al. | May 2006 | B2 |
| 7058788 | Niles et al. | Jun 2006 | B2 |
| 7058826 | Fung | Jun 2006 | B2 |
| 7069468 | Olson et al. | Jun 2006 | B1 |
| 7072916 | Lewis et al. | Jul 2006 | B1 |
| 7085899 | Kim et al. | Aug 2006 | B2 |
| 7085956 | Petersen et al. | Aug 2006 | B2 |
| 7089395 | Jacobson et al. | Aug 2006 | B2 |
| 7092977 | Leung et al. | Aug 2006 | B2 |
| 7093158 | Barron et al. | Aug 2006 | B2 |
| 7093161 | Mambakkam et al. | Aug 2006 | B1 |
| 7100080 | Howe | Aug 2006 | B2 |
| 7103740 | Colgrove et al. | Sep 2006 | B1 |
| 7103798 | Morita | Sep 2006 | B2 |
| 7107417 | Gibble et al. | Sep 2006 | B2 |
| 7111084 | Tan et al. | Sep 2006 | B2 |
| 7111147 | Strange et al. | Sep 2006 | B1 |
| 7124272 | Kennedy et al. | Oct 2006 | B1 |
| 7127633 | Olson et al. | Oct 2006 | B1 |
| 7133884 | Murley et al. | Nov 2006 | B1 |
| 7134011 | Fung | Nov 2006 | B2 |
| 7134053 | Moore | Nov 2006 | B1 |
| 7162587 | Hiken et al. | Jan 2007 | B2 |
| 7162599 | Berkowitz et al. | Jan 2007 | B2 |
| 7181581 | Burkey | Feb 2007 | B2 |
| 7184933 | Prekeges et al. | Feb 2007 | B2 |
| 7191304 | Cameron et al. | Mar 2007 | B1 |
| 7194653 | Hadders et al. | Mar 2007 | B1 |
| 7197614 | Nowakowski | Mar 2007 | B2 |
| 7216258 | Ebsen et al. | May 2007 | B2 |
| 7222205 | Jones et al. | May 2007 | B2 |
| 7225317 | Glade et al. | May 2007 | B1 |
| 7228441 | Fung | Jun 2007 | B2 |
| 7237129 | Fung | Jun 2007 | B2 |
| 7251713 | Zhang | Jul 2007 | B1 |
| 7254813 | Leong et al. | Aug 2007 | B2 |
| 7272666 | Rowan et al. | Sep 2007 | B2 |
| 7272735 | Fung | Sep 2007 | B2 |
| 7293196 | Hiken et al. | Nov 2007 | B2 |
| 7305579 | Williams | Dec 2007 | B2 |
| 7320052 | Zimmer et al. | Jan 2008 | B2 |
| 7380113 | Ebsen et al. | May 2008 | B2 |
| 7398418 | Soran et al. | Jul 2008 | B2 |
| 7404102 | Soran et al. | Jul 2008 | B2 |
| 7406631 | Moore | Jul 2008 | B2 |
| 7424637 | Schoenthal et al. | Sep 2008 | B1 |
| 7457982 | Rajan | Nov 2008 | B2 |
| 7475098 | Patterson et al. | Jan 2009 | B2 |
| 7484111 | Fung | Jan 2009 | B2 |
| 7493514 | Soran et al. | Feb 2009 | B2 |
| 7512822 | Fung | Mar 2009 | B2 |
| 7533283 | Fung | May 2009 | B2 |
| 7539991 | Leong et al. | May 2009 | B2 |
| 7552350 | Fung | Jun 2009 | B2 |
| 7558976 | Fung | Jul 2009 | B2 |
| 7562239 | Fung | Jul 2009 | B2 |
| 7574622 | Soran et al. | Aug 2009 | B2 |
| 7603532 | Rajan et al. | Oct 2009 | B2 |
| 7613945 | Soran et al. | Nov 2009 | B2 |
| 7672226 | Shea | Mar 2010 | B2 |
| 7702948 | Kalman et al. | Apr 2010 | B1 |
| 7849352 | Soran et al. | Dec 2010 | B2 |
| 7945810 | Soran et al. | May 2011 | B2 |
| 7962778 | Soran et al. | Jun 2011 | B2 |
| 8046469 | Lubbers et al. | Oct 2011 | B2 |
| 8555108 | Soran et al. | Oct 2013 | B2 |
| 20010020282 | Murotani et al. | Sep 2001 | A1 |
| 20020004912 | Fung | Jan 2002 | A1 |
| 20020004913 | Fung | Jan 2002 | A1 |
| 20020004915 | Fung | Jan 2002 | A1 |
| 20020007438 | Lee | Jan 2002 | A1 |
| 20020007463 | Fung | Jan 2002 | A1 |
| 20020007464 | Fung | Jan 2002 | A1 |
| 20020046320 | Shaath | Apr 2002 | A1 |
| 20020053009 | Selkirk et al. | May 2002 | A1 |
| 20020056031 | Skiba et al. | May 2002 | A1 |
| 20020062454 | Fung | May 2002 | A1 |
| 20020073278 | McDowell | Jun 2002 | A1 |
| 20020087813 | Harris et al. | Jul 2002 | A1 |
| 20020095546 | Dimitri et al. | Jul 2002 | A1 |
| 20020103969 | Koizumi et al. | Aug 2002 | A1 |
| 20020112113 | Karpoff et al. | Aug 2002 | A1 |
| 20020129214 | Sarkar | Sep 2002 | A1 |
| 20020129216 | Collins | Sep 2002 | A1 |
| 20020166079 | Ulrich et al. | Nov 2002 | A1 |
| 20020186492 | Smith | Dec 2002 | A1 |
| 20020188768 | Hirakawa et al. | Dec 2002 | A1 |
| 20020199129 | Bohrer et al. | Dec 2002 | A1 |
| 20030005248 | Selkirk et al. | Jan 2003 | A1 |
| 20030009619 | Kano et al. | Jan 2003 | A1 |
| 20030033577 | Anderson | Feb 2003 | A1 |
| 20030046270 | Leung et al. | Mar 2003 | A1 |
| 20030065901 | Krishnamurthy | Apr 2003 | A1 |
| 20030079014 | Lubbers et al. | Apr 2003 | A1 |
| 20030110263 | Shillo | Jun 2003 | A1 |
| 20030140207 | Nagase et al. | Jul 2003 | A1 |
| 20030182301 | Patterson et al. | Sep 2003 | A1 |
| 20030182503 | Leong et al. | Sep 2003 | A1 |
| 20030188097 | Holland et al. | Oct 2003 | A1 |
| 20030188114 | Lubbers et al. | Oct 2003 | A1 |
| 20030188208 | Fung | Oct 2003 | A1 |
| 20030200473 | Fung | Oct 2003 | A1 |
| 20030212865 | Hiken et al. | Nov 2003 | A1 |
| 20030212872 | Patterson et al. | Nov 2003 | A1 |
| 20030221060 | Umberger et al. | Nov 2003 | A1 |
| 20030231529 | Hetrick et al. | Dec 2003 | A1 |
| 20040015655 | Willis et al. | Jan 2004 | A1 |
| 20040030822 | Rajan et al. | Feb 2004 | A1 |
| 20040030951 | Armangau | Feb 2004 | A1 |
| 20040068522 | Daniels et al. | Apr 2004 | A1 |
| 20040068637 | Nelson et al. | Apr 2004 | A1 |
| 20040073747 | Lu | Apr 2004 | A1 |
| 20040088505 | Watanabe | May 2004 | A1 |
| 20040107222 | Venkatesh et al. | Jun 2004 | A1 |
| 20040107315 | Watanabe et al. | Jun 2004 | A1 |
| 20040111558 | Kistler et al. | Jun 2004 | A1 |
| 20040117572 | Welsh et al. | Jun 2004 | A1 |
| 20040133742 | Vasudevan et al. | Jul 2004 | A1 |
| 20040163009 | Goldstein et al. | Aug 2004 | A1 |
| 20040172577 | Tan et al. | Sep 2004 | A1 |
| 20050010618 | Hayden | Jan 2005 | A1 |
| 20050010731 | Zalewki et al. | Jan 2005 | A1 |
| 20050027938 | Burkey | Feb 2005 | A1 |
| 20050055603 | Soran et al. | Mar 2005 | A1 |
| 20050065962 | Rowan et al. | Mar 2005 | A1 |
| 20050081086 | Williams | Apr 2005 | A1 |
| 20050108582 | Fung | May 2005 | A1 |
| 20050114350 | Rose et al. | May 2005 | A1 |
| 20050144512 | Ming | Jun 2005 | A1 |
| 20050166085 | Thompson et al. | Jul 2005 | A1 |
| 20050182992 | Land et al. | Aug 2005 | A1 |
| 20050193058 | Yasuda et al. | Sep 2005 | A1 |
| 20050262325 | Shmueli et al. | Nov 2005 | A1 |
| 20060031287 | Ulrich | Feb 2006 | A1 |
| 20060041718 | Ulrich et al. | Feb 2006 | A1 |
| 20060059306 | Tseng | Mar 2006 | A1 |
| 20060093282 | Shepherd et al. | May 2006 | A1 |
| 20060107006 | Green et al. | May 2006 | A1 |
| 20060107097 | Zohar et al. | May 2006 | A1 |
| 20060161752 | Burkey | Jul 2006 | A1 |
| 20060161808 | Burkey | Jul 2006 | A1 |
| 20060179218 | Burkey | Aug 2006 | A1 |
| 20060184821 | Hitz et al. | Aug 2006 | A1 |
| 20060206536 | Sawdon et al. | Sep 2006 | A1 |
| 20060206665 | Orsley | Sep 2006 | A1 |
| 20060206675 | Sato et al. | Sep 2006 | A1 |
| 20060218360 | Burkey | Sep 2006 | A1 |
| 20060218367 | Ukai et al. | Sep 2006 | A1 |
| 20060218433 | Williams | Sep 2006 | A1 |
| 20060230244 | Amarendran et al. | Oct 2006 | A1 |
| 20060248324 | Fung | Nov 2006 | A1 |
| 20060248325 | Fung | Nov 2006 | A1 |
| 20060248358 | Fung | Nov 2006 | A1 |
| 20060248359 | Fung | Nov 2006 | A1 |
| 20060248360 | Fung | Nov 2006 | A1 |
| 20060248361 | Fung | Nov 2006 | A1 |
| 20060248379 | Jernigan, IV | Nov 2006 | A1 |
| 20060253669 | Lobdell | Nov 2006 | A1 |
| 20060253717 | Fung | Nov 2006 | A1 |
| 20060259797 | Fung | Nov 2006 | A1 |
| 20060265608 | Fung | Nov 2006 | A1 |
| 20060265609 | Fung | Nov 2006 | A1 |
| 20060271604 | Shoens | Nov 2006 | A1 |
| 20060277361 | Sharma et al. | Dec 2006 | A1 |
| 20060277432 | Patel et al. | Dec 2006 | A1 |
| 20070005885 | Kobayashi et al. | Jan 2007 | A1 |
| 20070011425 | Sicola | Jan 2007 | A1 |
| 20070016749 | Nakamura et al. | Jan 2007 | A1 |
| 20070016754 | Testardi | Jan 2007 | A1 |
| 20070101173 | Fung | May 2007 | A1 |
| 20070168709 | Morita | Jul 2007 | A1 |
| 20070180306 | Soran et al. | Aug 2007 | A1 |
| 20070220313 | Katsuragi et al. | Sep 2007 | A1 |
| 20070234109 | Soran et al. | Oct 2007 | A1 |
| 20070234110 | Soran et al. | Oct 2007 | A1 |
| 20070234111 | Soran et al. | Oct 2007 | A1 |
| 20070240006 | Fung | Oct 2007 | A1 |
| 20070245084 | Yagisawa et al. | Oct 2007 | A1 |
| 20070245165 | Fung | Oct 2007 | A1 |
| 20070260830 | Faibish et al. | Nov 2007 | A1 |
| 20070266066 | Kapoor et al. | Nov 2007 | A1 |
| 20070288401 | Hood et al. | Dec 2007 | A1 |
| 20080005468 | Faibish et al. | Jan 2008 | A1 |
| 20080091877 | Klemm et al. | Apr 2008 | A1 |
| 20080104139 | Xu et al. | May 2008 | A1 |
| 20080244172 | Kano | Oct 2008 | A1 |
| 20080288546 | Adkins et al. | Nov 2008 | A1 |
| 20090083563 | Murase | Mar 2009 | A1 |
| 20090132616 | Winter et al. | May 2009 | A1 |
| 20090132617 | Soran et al. | May 2009 | A1 |
| 20090138755 | Soran et al. | May 2009 | A1 |
| 20090235104 | Fung | Sep 2009 | A1 |
| 20090300412 | Soran et al. | Dec 2009 | A1 |
| 20100037023 | Aszmann et al. | Feb 2010 | A1 |
| 20110258388 | Soran et al. | Oct 2011 | A1 |
| 20120124285 | Soran et al. | May 2012 | A1 |
| 20120166725 | Soran et al. | Jun 2012 | A1 |
| 20120221683 | Ferris | Aug 2012 | A1 |
| 20130238854 | Edwards et al. | Sep 2013 | A1 |
| 20140108858 | Soran et al. | Apr 2014 | A1 |
| Number | Date | Country |
|---|---|---|
| 0757317 | Feb 1997 | EP |
| 0780758 | Jun 1997 | EP |
| 1462927 | Sep 2004 | EP |
| 0706113 | Aug 2005 | EP |
| 2373075 | Sep 2002 | GB |
| 1790351987 | Aug 1987 | JP |
| 3259320 | Nov 1991 | JP |
| 732211993 | Mar 1993 | JP |
| 1872011994 | Jul 1994 | JP |
| 07084839 | Mar 1995 | JP |
| 847321995 | Mar 1995 | JP |
| 7200367 | Aug 1995 | JP |
| 844503 | Feb 1996 | JP |
| 8278850 | Oct 1996 | JP |
| 443811997 | Feb 1997 | JP |
| 690281997 | Mar 1997 | JP |
| 9128305 | May 1997 | JP |
| 1283051997 | May 1997 | JP |
| 5108061997 | Oct 1997 | JP |
| 2546281998 | Sep 1998 | JP |
| 1341171999 | May 1999 | JP |
| 3278031999 | Nov 1999 | JP |
| 2000132343 | May 2000 | JP |
| 2000163290 | Jun 2000 | JP |
| 2000507014 | Jun 2000 | JP |
| 2001051882 | Feb 2001 | JP |
| 2001067187 | Mar 2001 | JP |
| 2001147785 | May 2001 | JP |
| 2001337850 | Dec 2001 | JP |
| 2001344139 | Dec 2001 | JP |
| 200232197 | Jan 2002 | JP |
| 200273393 | Mar 2002 | JP |
| 2002082775 | Mar 2002 | JP |
| 2002182860 | Jun 2002 | JP |
| 2002278819 | Sep 2002 | JP |
| 2002366398 | Dec 2002 | JP |
| 200315915 | Jan 2003 | JP |
| 200350724 | Feb 2003 | JP |
| 2003108317 | Apr 2003 | JP |
| 2003196127 | Jul 2003 | JP |
| 2004272324 | Sep 2004 | JP |
| 2005018612 | Jan 2005 | JP |
| 2005512191 | Apr 2005 | JP |
| 2006024024 | Jan 2006 | JP |
| 9523376 | Aug 1995 | WO |
| 9735269 | Sep 1997 | WO |
| 0013077 | Mar 2000 | WO |
| 0225445 | Mar 2002 | WO |
| 03014909 | Feb 2003 | WO |
| 03028183 | Apr 2003 | WO |
| 03048941 | Jun 2003 | WO |
| 03050707 | Jun 2003 | WO |
| 2005017737 | Feb 2005 | WO |
| Entry |
|---|
| The Compaq Enterprise Network Storage Architecture: An Overview, source(s): Compaq, May 2000, pp. 1-22. |
| Massiglia, P., “Chapter 11: Dynamic Data Mapping”, The RAIDbook. A Source for RAID Technology, Feb. 1997; pp. 197-208. |
| Wilkes, John, et al. “The HP AutoRAID Hierarchical Storage System”, ACM Transactions on Computer Systems, Association for Computing Machinery, ACM Transactions on Computer Systems, vol. 14, No. 1, Feb. 1996, pp. 108-136. |
| The PC Guide, “RAID Level 7”, 2001, Retrieved from http://www.pcguide.com/ref/hdd/perf/raid/levels/singleLevel7-c.html on Sep. 13, 2010, 3 pp. |
| Bolosky, W. J. et al. “Distributed Schedule Management in the Tiger Video Fileserver”, Abstract 1997, 212-223. |
| Cheung, L. “Design and Optimization of Distributed RAID Storage Systems”, Research Paper, CS555 Section A, Fall 2002 (15 pp.). |
| Jin, H. et al. “Improving Partial Stripe Write Performance in Raid Level 5”, Department of Computer Science and Technology, Huazong University of Science and Technology, Wuhan, 430074, P.R. China 1999, pp. 396-400. |
| Scheuermann, P. et al. “Data Partitioning and Load Balancing in Parallel Disk Systems”, Springer-Verlug 1998 (9 pp.). |
| Schomaker, G. et al. “DHHT-RAID: A Distributed Heterogenous Scalable Architecture for Dynamic Storage Environments”, 21st International Conference on Advanced Networking and Applications (AINA '07) 2007 (9 pp.). |
| Thomasian, A. et al. “A Performance Evaluation Tool for RAID Disk Arrays”, source(s): New Jersey Institute of Technology—NJIT, Proceeding of the First International Conference on the Quantitative Evaluation of Systems (QEST'04), Sep. 27-30, 2004, 10 pp. |
| Menon, J. et al. “Algorithms for Software and Low-Cost Hardware RAIDs”, IBM Almaden Research Center, menonjm@almaden.ibm.com, Copyright 1995, pp. 411-418. |
| Zadok, E. et al. “Reducing Storage Management Costs via Informed User-Based Policies”, Technical Report FSL-03-01, Aug. 14, 2003 (26 pp.). |
| Hwang, K. et al. “Orthogonal Striping and Mirroring in Distributed RAID for I/O-Centric Cluster Computing”, IEEE Transactions on Parallel and Distributed Systems, vol. 13, No. 1, Jan. 2002, pp. 26-44. |
| Loazia, J. “Optimal storage configuration made easy”, White paper 295, Oracle Corporation, Redwood Shores, CA, 2002. |
| Thornock, Niki et al. “A stochastic I/O simulation technique”, Proceedings of the 29th conference on Winter simulation (WSC '97), Dec. 7-10, 1997. IEEE Computer Society, Washington, D.C., U.S.A., pp. 1079-1086. |
| PCGuide article “Logical Block Addressing” [online]. 2001 [retrieved on Jun. 26, 2011]. Retrieved from the Internet: <URL:http://www.pcguide.com/ref/hdd/bios/modesLBA-c.html>. |
| Vongsathorn, P. et al. (1990) “A system for adaptive disk rearrangement”, Software: Practice and Experience, 20: 225-242. |
| Akyurek S. et al. “Adaptive block rearrangement”, ACM Trans. Comput. Syst. 13, 2 (May 1995), pp. 89-121. |
| Sarhan, N.J. “Adaptive block rearrangement algorithms for video-on-demand server,” Parallel Processing, International Conference on, 2001. vol., no. pp. 452-459, Sep. 3-7, 2001 doi: 10.1109/ICPP.2001.952092 URL:<http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=arnumber=952092&isnumber=20585>. |
| Geist, Robert et al. (1992) “Disk performance enhancement through Markov-based cylinder remapping”, Proceedings of the 30th annual Southeast regional conference (ACM-SE 30). ACM, New York, NY, USA, 23-28. |
| Vakali, Athena et al. “Data placement schemes in replicated mirrored disk systems”, Journey of Systems and Software, vol. 55, Issue 2, Dec. 27, 2000, pp. 115-128, ISSN 0164-1212, DOI: 10.1016/S0164-1212(00)00065-0. <http://www.sciencedirect.com/science/article/pii/S0164121200000650>. |
| Mogi, Kazuhiko, “Performance Tuning Function in RAID Device”, Technical Report of the Institute of Electronics, Information and Communication Engineers, vol. 101, No. 342, Japan, Institute of Electronics, Information, and Communication Engineers, Oct. 4, 2001, pp. 9-16. |
| Kim, Jeong-Won et al. “An Effective Video Block Placement Scheme on VOD Server Based on Multi-zone Recording Disks”, IEEE International Conference of Multimedia Computing and Systems '97, Jun. 3-6, 1997, pp. 29-36. |
| Wang, Jun et al. “PROFS-Performance-Oriented Data Reorganziation for Log-structured File System on Multi-zone Disks”, Ninth International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, Aug. 15-18, 2001, pp. 285-292. |
| Number | Date | Country | |
|---|---|---|---|
| 20140040546 A1 | Feb 2014 | US |
| Number | Date | Country | |
|---|---|---|---|
| 60495204 | Aug 2003 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 13104299 | May 2011 | US |
| Child | 14047152 | US | |
| Parent | 12538509 | Aug 2009 | US |
| Child | 13104299 | US | |
| Parent | 11689847 | Mar 2007 | US |
| Child | 12538509 | US | |
| Parent | 10918329 | Aug 2004 | US |
| Child | 11689847 | US |
