Optimal Content Caching and Recommendation With Age of Information

Abstract

Content caching at the network edge is an effective way of mitigating backhaul load and improving user experience. Caching efficiency can be enhanced by content recommendation and by keeping the information fresh. By content recommendation, a requested content that is not in the cache can be alternatively satisfied by a related cached content recommended by the system. Information freshness can be quantified by age of information (AoI). This paper has the following contributions. First, we address optimal scheduling of cache updates for a time-slotted system accounting for content recommendation and AoI, and to the best of our knowledge, there is no work that has jointly taken into account these aspects. Next, we rigorously prove the problem's NP-hardness. Then, we derive an integer linear formulation, by which the optimal solution can be obtained for small-scale scenarios. On the algorithmic side, our contributions include the development of an effective algorithm based on Lagrangian decomposition, and efficient algorithms for solving the resulting subproblems. Our algorithm computes a bound that can be used to evaluate the performance of any suboptimal solution. We conduct simulations to show the effectiveness of our algorithm.