Network Convergence & Security Laboratory

Abstract

Video dominates Internet traffic today. Users retrieve on-demand video from Content Delivery Networks (CDNs) which cache video chunks at front-ends. In this paper, we describe AViC, a caching algorithm that leverages properties of video delivery, such as request predictability and the presence of highly unpopular chunks. AViC’s eviction policy exploits request predictability to estimate a chunk’s future request time and evict the chunk with the furthest future request time. Its admission control policy uses a classifier to predict singletons — chunks evicted before a second reference. Using real world CDN traces from a commercial video service, we show that AViC outperforms a range of algorithm including LRU, GDSF, AdaptSize and LHD. In particular LRU requires up to 3.5× the cache size to match AViC’s performance. Further, AViC has low time complexity and has memory complexity comparable to GDSF

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