Spatial multi-LRU Caching for Wireless Networks with Coverage Overlaps

TL;DR

This paper proposes decentralized spatial multi-LRU caching policies for wireless networks with overlapping coverage, improving content diversity and hit probability, especially as multi-coverage increases, with variations suited for different traffic types.

Contribution

It introduces two novel multi-LRU caching policies for wireless edge networks, with spatial approximations for accurate performance prediction under IRM.

Findings

Multi-LRU performance improves with larger multi-coverage areas.

Multi-LRU-One outperforms Multi-LRU-All under IRM traffic.

Multi-LRU-All can perform better with temporal locality traffic.

Abstract

This article introduces a novel family of decentralised caching policies, applicable to wireless networks with finite storage at the edge-nodes (stations). These policies are based on the Least-Recently-Used replacement principle, and are, here, referred to as spatial multi-LRU. Based on these, cache inventories are updated in a way that provides content diversity to users who are covered by, and thus have access to, more than one station. Two variations are proposed, namely the multi-LRU-One and -All, which differ in the number of replicas inserted in the involved caches. By introducing spatial approximations, we propose a Che-like method to predict the hit probability, which gives very accurate results under the Independent Reference Model (IRM). It is shown that the performance of multi-LRU increases the more the multi-coverage areas increase, and it approaches the performance of other proposed centralised policies, when multi-coverage is sufficient. For IRM traffic multi-LRU-One outperforms multi-LRU-All, whereas when the traffic exhibits temporal locality the -All variation can perform better.