A Utility Optimization Approach to Network Cache Design

TL;DR

This paper introduces a utility-driven caching framework that optimizes cache content based on content-specific utilities, enabling tailored policies and reverse engineering classical algorithms like LRU and FIFO.

Contribution

It formulates utility-based cache optimization problems and develops online algorithms for implementing customizable caching policies.

Findings

Framework can reverse engineer classical policies like LRU and FIFO.

Optimization problems maximize total utility under cache constraints.

Online algorithms enable practical utility-based cache management.

Abstract

In any caching system, the admission and eviction policies determine which contents are added and removed from a cache when a miss occurs. Usually, these policies are devised so as to mitigate staleness and increase the hit probability. Nonetheless, the utility of having a high hit probability can vary across contents. This occurs, for instance, when service level agreements must be met, or if certain contents are more difficult to obtain than others. In this paper, we propose utility-driven caching, where we associate with each content a utility, which is a function of the corresponding content hit probability. We formulate optimization problems where the objectives are to maximize the sum of utilities over all contents. These problems differ according to the stringency of the cache capacity constraint. Our framework enables us to reverse engineer classical replacement policies such as LRU and FIFO, by computing the utility functions that they maximize. We also develop online algorithms that can be used by service providers to implement various caching policies based on arbitrary utility functions.