Caching with Time Domain Buffer Sharing

In this paper, storage efficient caching based on time domain buffer sharing is considered. The caching policy allows a user's device to determine whether and how long it should cache a content item according to the prediction of the user's random request time, also referred to as the request delay information (RDI). In particular, the aim is to maximize the caching gain for communications while limiting its storage cost. To achieve this goal, a queueing theoretic model for caching with infinite buffers is first formulated, in which Little's law is adopted to obtain the tradeoff between the hit ratio and the average buffer consumption. When there are multiple content classes with different RDIs, the storage efficiency is further optimized by carefully allocating the storage cost. For more practical finite-buffer caching, a G/GI/L/0 queue model is formulated, in which a diffusion approximation and the Erlang-B formula are adopted to determine the buffer overflow probability and the corresponding hit ratio. The optimal hit ratio is shown to be limited by the demand probability and buffer size for large and small buffers respectively. In practice, a user may exploit probabilistic caching with random maximum caching time and arithmetic caching without any need for content arrival statistics to efficiently harvest content files from the air.