Efficient Traffic Load-Balancing via Incremental Expansion of Routing Choices

Abstract

Routing policies play a major role in the performance of communication networks. Backpressure-based adaptive routing algorithms where traffic is load balanced along different routing paths on a per-packet basis have been studied extensively in the literature. Although backpressure-based algorithms have been shown to be networkwide throughput optimal, they typically have poor delay performance under light or moderate loads, because packets may be sent over unnecessarily long routes. Further, backpressure-based algorithms have required every node to compute differential backlogs for every per-destination queue with the corresponding per-destination queue at every adjacent node, which is expensive given the large number of possible pairwise differential backlogs between neighbor nodes. In this article, we propose new backpressure-based adaptive routing algorithms that only use shortest-path routes to destinations when they are sufficient to accommodate the given traffic load, but the proposed algorithms will incrementally expand routing choices as needed to accommodate increasing traffic loads. We show analytically by means of fluid analysis that the proposed algorithms retain networkwide throughput optimality, and we show empirically by means of simulations that our proposed algorithms provide substantial improvements in delay performance. Our evaluations further show that, in practice, our approach dramatically reduces the number of pairwise differential backlogs that have to be computed and the amount of corresponding backlog information that has to be exchanged, because routing choices are only incrementally expanded as needed.