Home // INFOCOMP 2012, The Second International Conference on Advanced Communications and Computation // View article
Authors:
Ryan Friese
Tyler Brinks
Curt Oliver
Howard Jay Siegel
Anthony A. Maciejewski
Keywords: bi-objective optimization; energy-aware; makespan; heterogeneous computing; resource allocation.
Abstract:
The energy consumption of data centers has been increasing rapidly over the past decade. In some cases, datacenters 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.
Pages: 81 to 89
Copyright: Copyright (c) IARIA, 2012
Publication date: October 21, 2012
Published in: conference
ISSN: 2308-3484
ISBN: 978-1-61208-226-4
Location: Venice, Italy
Dates: from October 21, 2012 to October 26, 2012