Designing Low-Complexity Heavy-Traffic Delay-Optimal Load Balancing Schemes: Theory to Algorithms

October 12, 2017 Β· Declared Dead Β· πŸ› Proceedings of the ACM on Measurement and Analysis of Computing Systems

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Authors Xingyu Zhou, Fei Wu, Jian Tan, Yin Sun, Ness Shroff arXiv ID 1710.04357 Category cs.DC: Distributed Computing Citations 32 Venue Proceedings of the ACM on Measurement and Analysis of Computing Systems Last Checked 6 months ago
Abstract
We establish a unified analytical framework for load balancing systems, which allows us to construct a general class $Ξ $ of policies that are both throughput optimal and heavy-traffic delay optimal. This general class $Ξ $ includes as special cases popular policies such as join-shortest-queue and power-of-$d$, but not the join-idle-queue (JIQ) policy. In fact, we show that JIQ, which is not in $Ξ $, is actually not heavy-traffic delay optimal. Owing to the significant flexibility offered by class $Ξ $, we are able to design a new policy called join-below-threshold (JBT-d), which maintains the simplicity of pull-based policies such as JIQ, but updates its threshold dynamically. We prove that JBT-$d$ belongs to the class $Ξ $ when the threshold is picked appropriately and thus it is heavy-traffic delay optimal. Extensive simulations show that the new policy not only has a low complexity in message rates, but also achieves excellent delay performance, comparable to the optimal join-shortest-queue in various system settings.
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