A Novel Centralized Strategy for Coded Caching with Non-uniform Demands

TL;DR

This paper proposes a new centralized caching strategy that allocates cache based on file popularity, enabling efficient coding across files with different popularities and improving performance over existing methods.

Contribution

Introduces a novel caching scheme that assigns more cache to popular files and allows linear coding across files without zero-padding, advancing nonuniform demand caching.

Findings

Noticeable improvement over state-of-the-art in a small example

Allows linear coding across files with different popularities

Maintains uniform sub-packetization for all files

Abstract

Despite significant progress in the caching literature concerning the worst case and uniform average case regimes, the algorithms for caching with nonuniform demands are still at a basic stage and mostly rely on simple grouping and memory-sharing techniques. In this work we introduce a novel centralized caching strategy for caching with nonuniform file popularities. Our scheme allows for assigning more cache to the files which are more likely to be requested, while maintaining the same sub-packetization for all the files. As a result, in the delivery phase it is possible to perform linear codes across files with different popularities without resorting to zero-padding or concatenation techniques. We will describe our placement strategy for arbitrary range of parameters. The delivery phase will be outlined for a small example for which we are able to show a noticeable improvement over the state of the art.