Improving Backpressure-based Adaptive Routing via Incremental Expansion of Routing Choices
Ping Yin, Sen Yang, Jun Jim Xu, Jim G. Dai, Bill Lin · 2017
Backpressure-based adaptive routing algorithms have been studied extensively in the literature. Although backpressure-based adaptive routing algorithms have been shown to be network-wide 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 destination queue with the corresponding destination queue at every adjacent node. This computation is expensive given the large number of possible pairwise differential backlogs and requires many exchanges of backlog information between adjacent nodes. In this paper, 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 network-wide 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.