Executing time and cost-aware task scheduling in hybrid cloud using a modified DE algorithm
by Yuanyuan Fan; Qingzhong Liang; Yunsong Chen; Xuesong Yan
International Journal of Computational Science and Engineering (IJCSE), Vol. 18, No. 3, 2019

Abstract: Task scheduling is one of the basic problems in cloud computing. In hybrid cloud, tasks scheduling faces new challenges. In this paper, we propose a GaDE algorithm, based on differential evolution algorithm, to improve single objective scheduling performance of a hybrid cloud. In order to better deal with the multi-objective task scheduling optimisation in hybrid clouds, on the basis of the GaDE and Pareto optimum of quick sorting method, we present a multi-objective algorithm, named NSjDE. This algorithm also makes considerations to reduce the frequency of evaluation. Comparing with experiments of Min-Min algorithm, GaDE algorithm and NSjDE algorithm, results show that for the single object task scheduling, GaDE and NsjDE algorithms perform better in getting the approximate optimal solution. The optimisation speed of multi-objective NSjDE algorithm is faster than the single-objective jDE algorithm, and NSjDE can produce more than one non-dominated solution meeting the requirements, in order to provide more options to the user.

Online publication date: Tue, 26-Mar-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com