Proximity-Aware Balanced Allocations in Cache Networks

TL;DR

This paper introduces a proximity-aware load balancing scheme for cache networks that reduces maximum load to logarithmic double-logarithmic scale while considering cache size and proximity constraints, outperforming traditional nearest-replica methods.

Contribution

It proposes a novel randomized load balancing scheme that accounts for cache size and proximity, achieving significant load reduction under certain conditions.

Findings

Maximum load of order Θ(log log n) in certain regimes

Exponential improvement over nearest available replica scheme

Low communication cost with the proposed scheme

Abstract

We consider load balancing in a network of caching servers delivering contents to end users. Randomized load balancing via the so-called power of two choices is a well-known approach in parallel and distributed systems that reduces network imbalance. In this paper, we propose a randomized load balancing scheme which simultaneously considers cache size limitation and proximity in the server redirection process. Since the memory limitation and the proximity constraint cause correlation in the server selection process, we may not benefit from the power of two choices in general. However, we prove that in certain regimes, in terms of memory limitation and proximity constraint, our scheme results in the maximum load of order $\Theta(\log\log n)$ (here $n$ is the number of servers and requests), and at the same time, leads to a low communication cost. This is an exponential improvement in the maximum load compared to the scheme which assigns each request to the nearest available replica. Finally, we investigate our scheme performance by extensive simulations.