Distributed Caching Algorithms in the Realm of Layered Video Streaming

Distributed caching architectures have been proposed for bringing content close to requesters, and the key problem is to design caching algorithms for reducing content delivery delay, which determines to an extent the user Quality of Experience (QoE). This problem obtains an interesting new twist with the advent of advanced layered-video encoding techniques such as Scalable Video Coding. In this paper, we show that the problem of finding the caching configuration of video encoding layers that minimizes delivery delay for a network operator is NP-Hard, and we establish a pseudopolynomial-time optimal solution by using a connection with the multiple-choice knapsack problem. Next, we design caching algorithms for multiple network operators that cooperate by pooling together their co-located caches, in an effort to aid each other, so as to avoid large delays due to fetching content from distant servers. We derive an approximate solution to this cooperative caching problem by using a technique that partitions the cache capacity into amounts dedicated to own and other operators' caching needs. Trace-driven evaluations demonstrate up to 25 percent reduction in delay over existing caching schemes. As a side benefit, our algorithms achieve smoother playback for video streaming applications, with fewer playback stalls and higher decoded quality.