An energy-efficient storage for video surveillance

With the rapid growth of the video surveillance applications, the storage energy consumption of video surveillance is more noticeable, but existed energy-saving methods for massive storage system most concentrate on the data centers mainly with random accesses. The storage of video surveillance has inherent access pattern, and requires special energy-saving approach to save more energy. An energy-efficient data layout for video surveillance, Semi-RAID is proposed. It adopts partial-parallelism strategy, which partitions disk data into different groups, and implements parallel accesses in each group. Grouping benefits to realize only partial disks working and the rest ones idle, and inner-group parallelism provides the performance guarantee. In addition, greedy strategy for address allocation is adopted to effectively prolong the idle period of the disks; particular Cache strategies are used to filter the small amount of random accesses. The energy-saving efficiency of Semi-RAID is verified by a simulated video surveillance consisting of 32 cameras with D1 resolution. The experiment shows: Semi-RAID can save 45 % energy than Hibernator; 80 % energy than PARAID; 33 % energy than MAID; 79 % energy than eRAID-5, while providing single disk fault tolerance and meeting the performance requirement, such as throughput.