Abstract
Coded caching is an effective technique to reduce peak network traffic load by exploiting coded multicasting opportunities among users with all possible requests. However, most existing works on coded caching design assume identical file sizes. In this paper, to fully exploit the coded multicasting opportunities in decentralized coded caching system with heterogenous file sizes, a file partitioning and grouping (FPG) scheme is proposed. In the FPG scheme, every file is divided into multiple subfiles, so that the subfiles of the same size from different files can be grouped into subfile groups. Based on the proposed FPG scheme, we formulate a placement optimized design problem to minimize the worst-case transmission load, in which we address how to allocate the limited cache sizes at users to different subfile groups. The optimal placement is found to be dependent on all file sizes and the cache size, as well as the number of subfile groups. The numerical results show that, the FPG scheme outperforms the existing decentralized coded caching schemes in the literature. Moreover, it can even approach the performance of the optimized centralized coded caching scheme when the number of files is smaller than the number of users.
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