A Learning Approach to Edge Caching with Dynamic Content Library in Wireless Networks

This paper focuses on joint edge cache placement and content delivery problem at a base station (BS) in the presence of spatio-temporal unknown content dynamics, where the BS can satisfy its users' content demands either directly from its local cache or by fetching from the content server. Unlike the previous works that assume a static content library, we consider a more realistic non-stationary scenario, where new contents are emerging over time at the content library and might be cached at users. We propose that the new contents cached at local users can be utilized by the BS to timely update its flexible portion of cache memory in addition to its routine off-peak main cache update from the content server. We model the caching problem as a non-stationary bandit problem and introduce a user-aided caching algorithm that accounts for the traffic demand variations and the limited caching space at the BS. The proposed algorithm progressively improves the caching policy, with the target of maximizing the weighted content delivery rate to the users in the long run. Simulation results validate that the proposed strategy outperforms various benchmark designs.