Quality of service task scheduling algorithm for time-cost trade off scheduling problem in cloud computing environment
by Danlami Gabi; Abdul Samad Ismail; Anazida Zainal; Zalmiyah Zakaria
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 18, No. 5, 2019

Abstract: In cloud computing environment, managing trade-offs between time and cost when executing large-scale tasks to guarantee customers minimum running time and cost of computation is not always feasible. Metaheuristics scheduling algorithms are considered as potential solutions but however, exhibit local trapping and imbalance between its global and local search. In this study, a multi-objective task scheduling model is first developed upon which a dynamic multi-objective orthogonal Taguchi-based cat swarm optimisation (dMOOTC) task scheduling algorithm is proposed to solve the model. In the developed dMOOTC algorithm, the Taguchi orthogonal approach and Pareto-optimisation strategy are used to reduced local trapping and balances between the global and local search which possibly increases its speed of convergence. Thirty independent simulation runs were conducted on CloudSim simulator tool. The results of the simulation showed that the dMOOTC scheduling algorithm showed a remarkable performance in minimising the time and cost compared to the benchmarked algorithms.

Online publication date: Mon, 02-Sep-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 Intelligent Systems Technologies and Applications (IJISTA):
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