Many-to-Many Matching Games for Proactive Social-Caching in Wireless Small Cell Networks

TL;DR

This paper models the caching problem in small cell networks as a many-to-many matching game, proposing a new algorithm that improves request satisfaction and reduces download times compared to random policies.

Contribution

It introduces a novel matching algorithm for caching in small cell networks and proves its stability, enhancing performance over existing random caching strategies.

Findings

Request satisfaction can be tripled with the proposed algorithm.

Download times are significantly reduced.

The algorithm guarantees pairwise stability.

Abstract

In this paper, we address the caching problem in small cell networks from a game theoretic point of view. In particular, we formulate the caching problem as a many-to-many matching game between small base stations and service providers' servers. The servers store a set of videos and aim to cache these videos at the small base stations in order to reduce the experienced delay by the end-users. On the other hand, small base stations cache the videos according to their local popularity, so as to reduce the load on the backhaul links. We propose a new matching algorithm for the many-to-many problem and prove that it reaches a pairwise stable outcome. Simulation results show that the number of satisfied requests by the small base stations in the proposed caching algorithm can reach up to three times the satisfaction of a random caching policy. Moreover, the expected download time of all the videos can be reduced significantly.