Data Orgnization Frequently accessed data on the same storage device?

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Presentation transcript:

Data Orgnization Frequently accessed data on the same storage device? Conversely, all infrequently accessed data on the same storage device? Retrieval efficiency through proper data placement Load balancing and availability issues

Storage Manager Allocation and storage of multimedia files on various storage devices (maintain metadata that maps logical blocks of files to physical blocks) Enforce bandwidth reservations on storage devices to ensure that devices are not overloaded Recover from hardware component failures Coordinate data storage on several hierarchies

Frames to Storage Blocks A one-to-one mapping between frames and blocks is inefficient Partitioning a multimedia file (viewed as a stream of bytes) into fixed-size storage blocks Extracting the frames from the storage blocks is left to the decoding software Convert frame rate to average block delivery rate

Data Block Placement Retrieval Blocks Contiguous Placement a single seek is enough (but fragmentation is a problem) Scattered Placement many intrafile seeks (can be alleviated using large block sizes and to read one block in each round) Constrained Placement intrafile seeks may be unavoidable if multiple blocks are needed in each round reduce the seeks to a reasonable bound by bounding the separation of successive blocks

Data Striping RAID Scheme -- data is striped across each disk achieves intrafile and interfile parallelism Disk arrays are a good solution to the high bandwidth requirements of multimedia services

RAID Data striping for improved peformance Redundancy for improved reliability Data striping distributes data over multiple disks to make them appear as a single, fast, large disk Multiple I/Os in parallel multiple requests on separate disks (decreases queueing time seen by I/O requests) single multiple block request on multiple disks (increases the effective transfer rate seen by a single request)