Energy Saving Task Scheduling Based on Optimized Ant Colony Algorithm in Cloud Environment

Authors

  • Haiqin Liu Department of Mathematics and Information Engineering, Dongchang College of Liaocheng University, Liaocheng 252000, China
  • Haifeng Yi Business School, Pingxiang University, Pingxiang 337055, China

Abstract

In a cloud environment, the majority of computational power requirements are concentrated in the cloud, resulting in higher energy consumption
for data centers. A method of reducing energy consumption while also reducing the time span of task scheduling has become an urgent problem to
be solved. In this paper, an optimal ant colony scheduling algorithm combined with a genetic algorithm is proposed, and an energy consumption
factor is introduced into the algorithm. Experiments show that this algorithm can effectively improve the time efficiency of task scheduling and reduce
energy consumption.

Keywords: Cloud computing; Task scheduling; Time span; Energy consumption; Genetic algorithm

Cite As

H. Liu, H. Yi, "Energy Saving Task Scheduling Based on Optimized Ant Colony Algorithm in Cloud Environment"
Engineering Intelligent Systems, vol. 29 no. 1, pp. 27-32, 2021.

Downloads

Published

2021-01-01

Issue

Vol. 29 No. 1 (2021): International Journal of Engineering Intelligent Systems

Section

General Submission

License

The submission of a paper implies that, if accepted for publication, it will not be published elsewhere in the same form, in any language, without the prior consent of the publisher. Before publication, authors are requested to assign copyright to CRL Publishing Ltd. This allows CRL to sanction photocopying, and to authorize the reprinting of issues or volumes according to demand. Authors' traditional rights will not be jeopardized by assigning Copyright in this way, as they retain the right to reuse the material following publication, and to veto third-party publication.