Multi-resolution video representation for parallel disk arrays

In a multimedia storage system video is probably the most demanding data type because of its large data volume and strict timing requirements. Image compression and parallel I/O architecture have been proposed in the literature to address the storage problem associated with digital video. This paper takes a systems approach by integrating video compression with data layout algorithms on parallel disk arrays to support high-quality video rendition. Specifically, we propose to use a multiresolution video representation scheme based on Gaussian and Laplacian Pyramids, which allows the storage system to satisfy video access requests by transferring only the minimum amount of data that is absolutely necessary. We also develope a new array storage layout algorithm for the Laplacian pyramid coding scheme to support jitter-free video rendering at the level of disk subsystems. We report on the results of a simulation study on the effectiveness of the proposed integrated design. The result shows that under the assumed workload the multi-resolution scheme is significantly better than the conventional representation in terms of the I/O rate, average waiting time, and average physical data bandwidth requirement. Specifically, the Laplacian Pyramid representation costs three to four times less data traffic, , reduces the average waiting time to one-eighth of that of the conventional approach, and achieves a five to ten times better average I/O rate.