Abstract: A streaming program execution method of an intelligent terminal is provided. The intelligent terminal does not store a program package of a program before the program is executed. The program package of the program includes a code segment, a read-only data segment, an uninitialized data segment, and a readable/writable data segment and is stored and managed by a server. The intelligent terminal obtains a program execution instruction, downloads the uninitialized data segment, the readable/writable data segment and the code segment of the program package from the server, loads the same into a local storage space and starts the execution of the program. During the execution process, according to a call request of the program on data of the code segment and the read-only data segment, the intelligent terminal downloads the requested data from the server and loads the data into the local storage space for the call of the program.

Abstract: A streaming program execution method of an intelligent terminal is provided. The intelligent terminal does not store a program package of a program before the program is executed. The program package of the program includes a code segment, a read-only data segment, an uninitialized data segment, and a readable/writable data segment and is stored and managed by a server. The intelligent terminal obtains a program execution instruction, downloads the uninitialized data segment, the readable/writable data segment and the code segment of the program package from the server, loads the same into a local storage space and starts the execution of the program. During the execution process, according to a call request of the program on data of the code segment and the read-only data segment, the intelligent terminal downloads the requested data from the server and loads the data into the local storage space for the call of the program.

Abstract: In a storage system, a control device determines that at least one first storage device of X storage devices is out of service. Then, the control device selects a second storage device from the X storage device. A quantity of stripe members of a data stripe stored in the second storage device is less than a ratio of T divided by X. The control device further writes target data into the second storage device. The target data is a data unit or a check unit used to update at least one stripe member of the data stripe stored in the first storage device.

Abstract: In a storage system, a control device determines that at least one first storage device of X storage devices is out of service. Then, the control device selects a second storage device from the X storage device. A quantity of stripe members of a data stripe stored in the second storage device is less than a ratio of T divided by X. The control device further writes target data into the second storage device. The target data is a data unit or a check unit used to update at least one stripe member of the data stripe stored in the first storage device.

Abstract: A solid state disk (SSD) caches disk-based volumes in a heterogeneous storage system, improving the overall storage-system performance. The hottest data blocks are identified based on two factors: the frequency of access, and temporal locality. Temporal locality is computed using a logarithmic system time. IO latency is reduced by migrating these hottest data blocks from hard-disk-based volumes to the solid-state flash-memory disks. Some dedicated mapping metadata and a novel top-K B-tree structure are used to index the blocks. Data blocks are ranked by awarding a higher current value for recent accesses, but also by the frequency of accesses. A non-trivial value for accesses in the past is retained by accumulating the two factors over many time spans expressed as a logarithmic system time. Having two factors, access frequency and the logarithmic system time, provides for a more balanced caching system.

Abstract: A solid state disk (SSD) caches disk-based volumes in a heterogeneous storage system, improving the overall storage-system performance. The hottest data blocks are identified based on two factors: the frequency of access, and temporal locality. Temporal locality is computed using a logarithmic system time. IO latency is reduced by migrating these hottest data blocks from hard-disk-based volumes to the solid-state flash-memory disks. Some dedicated mapping metadata and a novel top-K B-tree structure are used to index the blocks. Data blocks are ranked by awarding a higher current value for recent accesses, but also by the frequency of accesses. A non-trivial value for accesses in the past is retained by accumulating the two factors over many time spans expressed as a logarithmic system time. Having two factors, access frequency and the logarithmic system time, provides for a more balanced caching system.

Abstract: A solid state disk (SSD) caches disk-based volumes in a heterogeneous storage system, improving the overall storage-system performance. The hottest data blocks are identified based on two factors: the frequency of access, and temporal locality. Temporal locality is computed using a logarithmic system time. IO latency is reduced by migrating these hottest data blocks from hard-disk-based volumes to the solid-state flash-memory disks. Some dedicated mapping metadata and a novel top-K B-tree structure are used to index the blocks. Data blocks are ranked by awarding a higher current value for recent accesses, but also by the frequency of accesses. A non-trivial value for accesses in the past is retained by accumulating the two factors over many time spans expressed as a logarithmic system time. Having two factors, access frequency and the logarithmic system time, provides for a more balanced caching system.