Reversing The Meaning of Node Connectivity for Content Placement in Networks of Caches

TL;DR

This paper challenges traditional heuristics in network caching by proposing a novel content placement strategy that prioritizes least connected nodes, supported by analytical results showing improved performance in simple topologies.

Contribution

It introduces a new content placement policy that reverses conventional connectivity-based heuristics and provides analytical validation for its effectiveness.

Findings

Least connected node placement outperforms traditional heuristics in regular grids and trees.

Analytical results demonstrate the benefits of the proposed policy under typical conditions.

The study offers a new perspective on content placement strategies in network caching.

Abstract

It is a widely accepted heuristic in content caching to place the most popular content at the nodes that are the best connected. The other common heuristic is somewhat contradictory, as it places the most popular content at the edge, at the caching nodes nearest the users. We contend that neither policy is best suited for caching content in a network and propose a simple alternative that places the most popular content at the least connected node. Namely, we populate content first at the nodes that have the lowest graph centrality over the network topology. Here, we provide an analytical study of this policy over some simple topologies that are tractable, namely regular grids and trees. Our mathematical results demonstrate that placing popular content at the least connected nodes outperforms the aforementioned alternatives in typical conditions.