We investigate the problem of coded caching for nonuniform demands when the structured clique cover algorithm proposed by Maddah-Ali and Niesen for decentralized caching is used for delivery. We apply this algorithm to all user demands regardless of their request probabilities. This allows for coding among the files that have different request probabilities but makes the allocation of memory to different files challenging during the content placement phase. As our main contribution, we analytically characterize the optimal placement strategy that minimizes the expected delivery rate under a storage capacity constraint. It is shown that the optimal placement follows either a two or a three group strategy, where a set of less popular files are not cached at all and the files within each of the other sets are allocated identical amounts of storage as if they had the same request probabilities. We show that for a finite set of storage capacities, that we call the base-cases of the problem, the two group strategy is always optimal. For other storage capacities, optimal placement is achieved by memory sharing between certain base-cases and the resulting placement either follows a two or a three group strategy depending on the corresponding base-cases used. We derive a polynomial time algorithm that determines the base-cases of the problem given the number of caches and popularity distribution of files. Given the base-cases of the problem, the optimal memory allocation parameters for any storage capacity are derived analytically. Index Terms-Coded caching, convex optimization, nonuniform demands, submodular functions.
Memory-sharing among such points must be performed if the cache size is not a member of M. The set of base-cases depends on the popularities of the files, the number of users and the number of files, and can be computed via an efficient algorithm REF .
Full Characterization of Optimal Uncoded Placement for the Structured Clique Cover Delivery of Nonuniform Demands
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Computer Science Mathematics