Dynamic Load Balancing with Tokens

TL;DR

This paper introduces a token-based load balancing mechanism for data centers that efficiently distributes jobs without prior knowledge of job arrival rates or server capacities, ensuring robustness and high resource utilization.

Contribution

The paper proposes a novel token-based load balancing method that is insensitive to job size distribution and does not require knowledge of system parameters.

Findings

The token mechanism effectively balances load without system parameter knowledge.

The approach is insensitive to job size distribution under balanced fair sharing.

Performance surpasses static load balancing and approaches ideal resource utilization.

Abstract

Efficiently exploiting the resources of data centers is a complex task that requires efficient and reliable load balancing and resource allocation algorithms. The former are in charge of assigning jobs to servers upon their arrival in the system, while the latter are responsible for sharing server resources between their assigned jobs. These algorithms should take account of various constraints, such as data locality, that restrict the feasible job assignments. In this paper, we propose a token-based mechanism that efficiently balances load between servers without requiring any knowledge on job arrival rates and server capacities. Assuming a balanced fair sharing of the server resources, we show that the resulting dynamic load balancing is insensitive to the job size distribution. Its performance is compared to that obtained under the best static load balancing and in an ideal system that would constantly optimize the resource utilization.