Video-on-demand services: Efficient transportation and decompression of variable bit rate video

Digital video compression techniques, such as the Motion-JPEG and MPEG compression standards, greatly reduce the network and storage requirements for digital video. These techniques, however, result in variable-bit-rate video which make the efficient handling and decompression of the video difficult. In this dissertation, we examine how variable-bit-rate digital video affects the ability to efficiently transport and decompress these videos. We introduce two new bandwidth smoothing techniques that reduce the resource requirements for the transportation of compressed video across networks: the critical bandwidth allocation algorithm, which, given a fixed buffer size, creates a bandwidth plan for the continuous playback of video that (1) requires no prefetching of data, (2) has the minimum number of bandwidth increases, and (3) minimizes the peak bandwidth requirements, and the optimal bandwidth allocation algorithm, which minimizes the total number of bandwidth changes required for continuous video playback. The use of bandwidth smoothing techniques in video-on-demand services results in plans that are somewhat inflexible. To allow users to have VCR capabilities in bandwidth smoothing environments, we analyze the utility of buffered video for decreasing the required interactions with the server. This buffered video, the VCR-window, allows users to have VCR capabilities within a limited without changing the bandwidth allocation levels. For accesses that cannot be serviced through the smoothing buffer, we show how contingency channels can be used to quickly return users to their original bandwidth allocation plans. Software video decompression algorithms have poor cache utilizations because of the long time between accesses to temporal data. We examine two techniques for reducing cache misses for software video decompression, reducing the working-set size and using software prefetching. To reduce the working-set size, we introduce several techniques that re-order the decompression algorithm to exploit the temporal accesses to data. These techniques reduce the cache miss rates by over 50% and can result in better performance. In addition, we examine the impact that software-controlled prefetching has on MPEG video decompression. Our results show that sufficient memory bandwidth exists for prefetching to be beneficial and that miss rates can be reduced by as much as 80%.