Cloud task scheduling based on ant colony optimization
Joint Authors
Tawfiq, Midhat
Arabi, Kishk
Turki, Fawzi
al-Sisi, Ashraf
Source
The International Arab Journal of Information Technology
Issue
Vol. 12, Issue 2 (31 Mar. 2015)9 p.
Publisher
Publication Date
2015-03-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Cloud computing is the development of distributed computing, parallel computing and grid computing, or defined as the commercial implementation of these computer science concepts.
One of the fundamental issues in this environment is related to task scheduling.
Cloud task scheduling is an NP-hard optimization problem, and many meta-heuristic algorithms have been proposed to solve it.
A good task scheduler should adapt its scheduling strategy to the changing environment and the types of tasks.
In this paper a cloud task scheduling policy based on ant colony optimization algorithm compared with different scheduling algorithms FCFS and round-robin, has been presented.
The main goal of these algorithms is minimizing the makespan of a given tasks set.
Ant colony optimization is random optimization search approach that will be used for allocating the incoming jobs to the virtual machines.
Algorithms have been simulated using Cloudsim toolkit package.
Experimental results showed that cloud task scheduling based on ant colony optimization outperformed FCFS and roundrobin algorithms.
American Psychological Association (APA)
Tawfiq, Midhat& al-Sisi, Ashraf& Arabi, Kishk& Turki, Fawzi. 2015. Cloud task scheduling based on ant colony optimization. The International Arab Journal of Information Technology،Vol. 12, no. 2.
https://search.emarefa.net/detail/BIM-368907
Modern Language Association (MLA)
Tawfiq, Midhat…[et al.]. Cloud task scheduling based on ant colony optimization. The International Arab Journal of Information Technology Vol. 12, no. 2 (Mar. 2015).
https://search.emarefa.net/detail/BIM-368907
American Medical Association (AMA)
Tawfiq, Midhat& al-Sisi, Ashraf& Arabi, Kishk& Turki, Fawzi. Cloud task scheduling based on ant colony optimization. The International Arab Journal of Information Technology. 2015. Vol. 12, no. 2.
https://search.emarefa.net/detail/BIM-368907
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references.
Record ID
BIM-368907