Jiangchuan LiuXiaowen ChuJianliang Xu
Caching video objects at proxies close to clients has attracted a lot of attention in recent years. To meet diverse client bandwidth conditions, there have been research efforts to combine proxy caching with video layering or transcoding. Nevertheless, these adaptive systems suffer from either coarse adaptation granularity due to the inflexible structures of existing layered coders or high computation overhead due to the transcoding operations. In this paper, we propose a novel adaptive video caching framework that enables low-cost and fine-grained adaptation. The innovative approach employs the MPEG-4 fine-grained scalable (FGS) video with postencoding rate control. We demonstrate that the proposed framework is both network aware and media adaptive: clients can be of heterogeneous streaming rates, and the backbone bandwidth consumption can be adaptively controlled. We also examine the design and management issues in the framework, in particular, the optimal stream portions to cache and the optimal streaming rate to each client. Simulation results demonstrate that, compared to nonadaptive caching, the proposed framework with optimal cache management not only achieves significant reduction on transmission costs but also enables flexible utility assignment for the heterogeneous clients. Meanwhile, its computational overhead is kept at a low level, implying that it is practically deployable.
Philippe de CuetosKeith W. Ross