Analyzing the Trade-offs Between Minimizing Makespan and Minimizing Energy Consumption in a Heterogeneous Resource Allocation Problem
Ryan D. Friese, Tyler Brinks, Curt Oliver, Howard Jay Siegel, Anthony A. Maciejewski · 2012
The energy consumption of data centers has been increasing rapidly over the past decade. In some cases, data centers may be physically limited by the amount of power available for consumption. Both the rising cost and physical limitations of available power are increasing the need for energy efficient computing. Data centers must be able to lower their energy consumption while maintaining a high level of performance. Minimizing energy consumption while maximizing performance can be modeled as a bi-objective optimization problem. In this paper, we develop a method to create different resource allocations that illustrate the trade- offs between minimizing energy consumed and minimizing the makespan of a system. By adapting a popular multi-objective genetic algorithm we are able to construct Pareto fronts (via simulation) consisting of Pareto-efficient resource allocations. We analyze different solutions from within the fronts to further understand the relationships between energy consumption and makespan. This information can allow system managers to make intelligent scheduling decisions based on the energy and performance needs of their system.