Optimal Content Replication and Request Matching in Large Caching Systems

TL;DR

This paper investigates optimal content replication and request matching in large caching systems constrained by memory and bandwidth, proposing algorithms with proven approximation guarantees and analyzing their asymptotic optimality.

Contribution

It formulates the optimal replication and matching problem, proves NP-hardness, and introduces practical algorithms with theoretical performance guarantees and asymptotic optimality.

Findings

Greedy replication scheme offers a constant factor approximation.

Proposed randomized matching scheme avoids request interruption.

Policies achieve asymptotic optimality in large-scale regimes.

Abstract

We consider models of content delivery networks in which the servers are constrained by two main resources: memory and bandwidth. In such systems, the throughput crucially depends on how contents are replicated across servers and how the requests of specific contents are matched to servers storing those contents. In this paper, we first formulate the problem of computing the optimal replication policy which if combined with the optimal matching policy maximizes the throughput of the caching system in the stationary regime. It is shown that computing the optimal replication policy for a given system is an NP-hard problem. A greedy replication scheme is proposed and it is shown that the scheme provides a constant factor approximation guarantee. We then propose a simple randomized matching scheme which avoids the problem of interruption in service of the ongoing requests due to re-assignment or repacking of the existing requests in the optimal matching policy. The dynamics of the caching system is analyzed under the combination of proposed replication and matching schemes. We study a limiting regime, where the number of servers and the arrival rates of the contents are scaled proportionally, and show that the proposed policies achieve asymptotic optimality. Extensive simulation results are presented to evaluate the performance of different policies and study the behavior of the caching system under different service time distributions of the requests.