Critical Database Size for Effective Caching

TL;DR

This paper investigates the limits of caching efficiency in networks, showing that caching's effectiveness diminishes as the number of files grows relative to the square of the number of users, and improves bounds on network load tradeoffs.

Contribution

It provides an improved outer bound on the network load versus cache memory tradeoff and analyzes caching effectiveness as the number of files increases.

Findings

Caching effectiveness diminishes when files are comparable to the square of users.

Improved bounds on network load and cache memory tradeoff.

Caching has limited benefits with very large file sets.

Abstract

Replicating or caching popular content in memories distributed across the network is a technique to reduce peak network loads. Conventionally, the performance gain of caching was thought to result from making part of the requested data available closer to end users. Recently, it has been shown that by using a carefully designed technique to store the contents in the cache and coding across data streams a much more significant gain can be achieved in reducing the network load. Inner and outer bounds on the network load v/s cache memory tradeoff were obtained in (Maddah-Ali and Niesen, 2012). We give an improved outer bound on the network load v/s cache memory tradeoff. We address the question of to what extent caching is effective in reducing the server load when the number of files becomes large as compared to the number of users. We show that the effectiveness of caching become small when the number of files becomes comparable to the square of the number of users.