Cooperative Caching for Multimedia Streaming in Overlay Networks

Traditional data caching, such as web caching, only focuses on how to boost the hit rate of requested objects in caches, and therefore, how to reduce the initial delay for object retrieval. However, for multimedia objects, not only reducing the delay of object retrieval, but also provisioning reasonably stable network bandwidth to clients, while the fetching of the cached objects goes on, is important as well. In this paper, we propose our cooperative caching scheme for a multimedia delivery scenario, supporting a large number of peers over peer-to-peer overlay networks. In order to facilitate multimedia streaming and downloading service from servers, our caching scheme (1) determines the appropriate availability of cached stream segments in a cache community, (2) determines the appropriate peer for cache replacement, and (3) performs bandwidth-aware and availability-aware cache replacement. By doing so, it achieves (1) small delay of stream retrieval, (2) stable bandwidth provisioning during retrieval session, and (3) load balancing of clients' requests among peers

Cooperative announcement-based caching for video-on-demand streaming

Recently, video-on-demand (VoD) streaming services like Netflix and Hulu have gained a lot of popularity. This has led to a strong increase in bandwidth capacity requirements in the network. To reduce this network load, the design of appropriate caching strategies is of utmost importance. Based on the fact that, typically, a video stream is temporally segmented into smaller chunks that can be accessed and decoded independently, cache replacement strategies have been developed that take advantage of this temporal structure in the video. In this paper, two caching strategies are proposed that additionally take advantage of the phenomenon of binge watching, where users stream multiple consecutive episodes of the same series, reported by recent user behavior studies to become the everyday behavior. Taking into account this information allows us to predict future segment requests, even before the video playout has started. Two strategies are proposed, both with a different level of coordination between the caches in the network. Using a VoD request trace based on binge watching user characteristics, the presented algorithms have been thoroughly evaluated in multiple network topologies with different characteristics, showing their general applicability. It was shown that in a realistic scenario, the proposed election-based caching strategy can outperform the state-of-the-art by 20% in terms of cache hit ratio while using 4% less network bandwidth