Caching Contents with Varying Popularity using Restless Bandits

TL;DR

This paper addresses the challenge of content caching at wireless edge nodes by modeling it as a restless bandit problem, deriving structural properties, and applying Whittle index policies to optimize caching decisions over time.

Contribution

It introduces a novel formulation of edge caching as a restless bandit problem, proving indexability and deriving a threshold-based optimal policy.

Findings

Proves the indexability of the caching problem.

Derives a threshold structure for the optimal policy.

Demonstrates the effectiveness of Whittle index policy in minimizing costs.

Abstract

Mobile networks are experiencing prodigious increase in data volume and user density , which exerts a great burden on mobile core networks and backhaul links. An efficient technique to lessen this problem is to use caching i.e. to bring the data closer to the users by making use of the caches of edge network nodes, such as fixed or mobile access points and even user devices. The performance of a caching depends on contents that are cached. In this paper, we examine the problem of content caching at the wireless edge(i.e. base stations) to minimize the discounted cost incurred over infinite horizon. We formulate this problem as a restless bandit problem, which is hard to solve. We begin by showing an optimal policy is of threshold type. Using these structural results, we prove the indexability of the problem, and use Whittle index policy to minimize the discounted cost.