Abstract
Content caching at the Internet edge using a network of wireless edge caching stations (ECSs) is recently considered as a key solution to alleviating the backhaul traffic burden and improving the quality of experience in 5G networks. This paper studies wireless edge caching systems with the following features: first, content files can be partitioned into many coded packets, which then can be cached in multiple ECSs for collaborative content delivery; second, the service provider (SP) deploys time-to-live cache at ECSs and each cached content file has an occupancy time that needs to be guaranteed; third, the content-to-be-cached arrives at the caching system following a stochastic process as users request new content over time. Unlike existing works that determine which content to cache, this paper focuses on how to distribute the coded packets of content-to-be-cached among the network of ECSs in order to reduce the content downloading time. A novel content placement strategy, called stochastic collaborative content placement is proposed based on Lyapunov techniques. The proposed algorithm makes content placement decisions using only currently available information without foreseeing future content arrivals, takes advantage of the spatial content popularity variation with coded caching, and achieves the provable close-to-optimal long-term caching performance. Simulations are carried out on a real-world YouTube video request trace and the results demonstrate a tremendous caching performance improvement against a variety of benchmark schemes.
