Evaluating load balancing policies for performance and energy-efficiency

TL;DR

This paper introduces a syntax for dynamic load balancing policies that optimize performance and energy efficiency in large server clusters, validated through implementations in iDSL and AnyLogic.

Contribution

It presents a new syntax for load balancing policies considering performance and energy trade-offs, with implementations and validation tools.

Findings

Validated load balancing policies through simulation and language tools

Demonstrated potential energy savings with dynamic server management

Provided a flexible framework for policy evaluation

Abstract

Nowadays, more and more increasingly hard computations are performed in challenging fields like weather forecasting, oil and gas exploration, and cryptanalysis. Many of such computations can be implemented using a computer cluster with a large number of servers. Incoming computation requests are then, via a so-called load balancing policy, distributed over the servers to ensure optimal performance. Additionally, being able to switch-off some servers during low period of workload, gives potential to reduced energy consumption. Therefore, load balancing forms, albeit indirectly, a trade-off between performance and energy consumption. In this paper, we introduce a syntax for load-balancing policies to dynamically select a server for each request based on relevant criteria, including the number of jobs queued in servers, power states of servers, and transition delays between power states of servers. To evaluate many policies, we implement two load balancers in: (i) iDSL, a language and tool-chain for evaluating service-oriented systems, and (ii) a simulation framework in AnyLogic. Both implementations are successfully validated by comparison of the results.