A Model Based Approach to Reachability Routing

TL;DR

This paper introduces reachability routing, a reinforcement learning-based approach designed for highly dynamic networks, providing cost-sensitive multi-path forwarding and loop avoidance within IP architecture, outperforming existing algorithms.

Contribution

It presents a novel reachability routing framework using reinforcement learning tailored for dynamic network topologies, addressing limitations of current routing protocols.

Findings

Consistently superior performance over other reinforcement learning routing algorithms.

Effective loop avoidance and multi-path forwarding in dynamic networks.

Validated on various network topologies.

Abstract

Current directions in network routing research have not kept pace with the latest developments in network architectures, such as peer-to-peer networks, sensor networks, ad-hoc wireless networks, and overlay networks. A common characteristic among all of these new technologies is the presence of highly dynamic network topologies. Currently deployed single-path routing protocols cannot adequately cope with this dynamism, and existing multi-path algorithms make trade-offs which lead to less than optimal performance on these networks. This drives the need for routing protocols designed with the unique characteristics of these networks in mind. In this paper we propose the notion of reachability routing as a solution to the challenges posed by routing on such dynamic networks. In particular, our formulation of reachability routing provides cost-sensitive multi-path forwarding along with loop avoidance within the confines of the Internet Protocol (IP) architecture. This is achieved through the application of reinforcement learning within a probabilistic routing framework. Following an explanation of our design decisions and a description of the algorithm, we provide an evaluation of the performance of the algorithm on a variety of network topologies. The results show consistently superior performance compared to other reinforcement learning based routing algorithms.