Distributed Dispatching in the Parallel Server Model

TL;DR

This paper introduces Tidal Water Filling, a novel distributed dispatching method for multi-dispatcher load balancing in cloud systems, which leverages information about other dispatchers to outperform existing solutions.

Contribution

It proposes a new distributed dispatching protocol that incorporates multiple dispatchers' information, significantly improving load balancing performance over existing methods.

Findings

Tidal Water Filling outperforms previous load balancing protocols.

Complete and accurate queue information enhances system performance.

The approach effectively addresses herding and incast issues.

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 queues, our policies significantly outperform all existing solutions.