Freshness-Aware Cache Update with Time-Varying Popularities in Edge Networks

Edge caching has been well recognized as a way of relieving the burden of networks but may lead to content staleness, calling for effective cache update. In this paper, we investigate a cache update problem in edge networks which downloads time-sensitive contents from a source with time-varying content popularity. Unlike previous works, we consider that different contents can have different popularity time scales. For contents which vary slowly over slots, many short-term update transmissions may occur during a slot. We formulate an update scheduling problem that optimizes the number of updates and the inter-update intervals within a slot for each content, in order to minimize the average age of information (AoI) of the requested contents. To tackle this problem efficiently, we reformulate and then decompose it into two sub-problems. Based on the theoretical results of the two sub-problems, we propose a practical update policy without the prior knowledge of content popularity. Compared with the widely known square-root law policy, simulations show that the proposed policy achieves a better performance.