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Scientific Programming
Volume 2016, Article ID 7040276, 10 pages
http://dx.doi.org/10.1155/2016/7040276
Research Article

A Heuristic Task Scheduling Algorithm for Heterogeneous Virtual Clusters

1School of Computer Science and Engineering, South China University of Technology, Guangdong, China
2School of Computing, Clemson University, P.O. Box 340974, Clemson, SC 29634-0974, USA

Received 27 January 2016; Accepted 20 April 2016

Academic Editor: Ligang He

Copyright © 2016 Weiwei Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Cloud computing provides on-demand computing and storage services with high performance and high scalability. However, the rising energy consumption of cloud data centers has become a prominent problem. In this paper, we first introduce an energy-aware framework for task scheduling in virtual clusters. The framework consists of a task resource requirements prediction module, an energy estimate module, and a scheduler with a task buffer. Secondly, based on this framework, we propose a virtual machine power efficiency-aware greedy scheduling algorithm (VPEGS). As a heuristic algorithm, VPEGS estimates task energy by considering factors including task resource demands, VM power efficiency, and server workload before scheduling tasks in a greedy manner. We simulated a heterogeneous VM cluster and conducted experiment to evaluate the effectiveness of VPEGS. Simulation results show that VPEGS effectively reduced total energy consumption by more than 20% without producing large scheduling overheads. With the similar heuristic ideology, it outperformed Min-Min and RASA with respect to energy saving by about 29% and 28%, respectively.