Congestion-aware routing and content placement in elastic cache networks

TL;DR

This paper develops algorithms for joint cache deployment, content placement, and routing in networks to minimize combined costs, effectively balancing congestion mitigation and resource expenditure.

Contribution

It introduces novel algorithms for both fixed and dynamic routing scenarios, providing approximation guarantees and demonstrating superior performance through simulations.

Findings

Algorithms outperform baseline techniques in simulations

Effective joint optimization reduces congestion and costs

Distributed online algorithm adapts to network dynamics

Abstract

Caching can be leveraged to significantly improve network performance and mitigate congestion. However, characterizing the optimal tradeoff between routing cost and cache deployment cost remains an open problem. In this paper, for a network with arbitrary topology and congestion-dependent nonlinear cost functions, we aim to jointly determine the cache deployment, content placement, and hop-by-hop routing strategies, so that the sum of routing cost and cache deployment cost is minimized. We tackle this NP-hard problem starting with a fixed-routing setting, and then to a general dynamic-routing setting. For the fixed-routing setting, a Gradient-combining Frank-Wolfe algorithm with $(\frac{1}{2},1)$-approximation is presented. For the general dynamic-routing setting, we obtain a set of KKT necessary optimal conditions, and devise a distributed and adaptive online algorithm based on the conditions. We demonstrate via extensive simulation that our algorithms significantly outperform a number of baseline techniques.