Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 589243, 16 pages
Research Article

Energy-Efficient Multi-Job Scheduling Model for Cloud Computing and Its Genetic Algorithm

1School of Computer Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China
2School of Computer Science and Technology, Zhoukou Normal University, Zhoukou 466001, China

Received 15 September 2011; Revised 19 October 2011; Accepted 19 October 2011

Academic Editor: Anders Eriksson

Copyright © 2012 Xiaoli Wang 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.


For the problem that the energy efficiency of the cloud computing data center is low, from the point of view of the energy efficiency of the servers, we propose a new energy-efficient multi-job scheduling model based on Google’s massive data processing framework. To solve this model, we design a practical encoding and decoding method for the individuals and construct an overall energy efficiency function of the servers as the fitness value of each individual. Meanwhile, in order to accelerate the convergent speed of our algorithm and enhance its searching ability, a local search operator is introduced. Finally, the experiments show that the proposed algorithm is effective and efficient.