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Distributed Dispatching in the Parallel Server Model

Authors Guy Goren , Shay Vargaftik , Yoram Moses



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Guy Goren
  • Technion - Israel Institute of Technology, Haifa, Israel
Shay Vargaftik
  • VMware Research
Yoram Moses
  • Technion - Israel Institute of Technology, Haifa, Israel

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Guy Goren, Shay Vargaftik, and Yoram Moses. Distributed Dispatching in the Parallel Server Model. In 34th International Symposium on Distributed Computing (DISC 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 179, pp. 14:1-14:18, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.DISC.2020.14

Abstract

With the rapid increase in the size and volume of cloud services and data centers, architectures with multiple job dispatchers are quickly becoming the norm. Load balancing is a key element of such systems. Nevertheless, current solutions to load balancing in such systems admit a paradoxical behavior in which more accurate information regarding server queue lengths degrades performance due to herding and detrimental incast effects. Indeed, both in theory and in practice, there is a common doubt regarding the value of information in the context of multi-dispatcher load balancing. As a result, both researchers and system designers resort to more straightforward solutions, such as the power-of-two-choices to avoid worst-case scenarios, potentially sacrificing overall resource utilization and system performance. A principal focus of our investigation concerns the value of information about queue lengths in the multi-dispatcher setting. We argue that, at its core, load balancing with multiple dispatchers is a distributed computing task. In that light, we propose a new job dispatching approach, called Tidal Water Filling, which addresses the distributed nature of the system. Specifically, by incorporating the existence of other dispatchers into the decision-making process, our protocols outperform previous solutions in many scenarios. In particular, when the dispatchers have complete and accurate information regarding the server queue lengths, our policies significantly outperform all existing solutions.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Distributed algorithms
  • Networks → Network algorithms
  • Theory of computation → Online algorithms
Keywords
  • Distributed load balancing
  • Join the Shortest Queue
  • Tidal Water Filling
  • Parallel Server Model

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