An Ant Algorithm for Cloud Task Scheduling

DOI

10.2991/ccis-13.2013.40How to use a DOI?

Keywords

Cloud computing; task scheduling; makespan; ant colony optimization; CloudSim

Abstract

Cloud computing is a type of parallel and distributed system consisting of a collection of interconnected and virtual computers. 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, modified ant colony optimization for cloud task scheduling is proposed. The goal of modification is to enhance the performance of the basic ant colony optimization algorithm and optimize the task execution time in view of minimizing the makespan of a given tasks set. Our approach proposes self-adapting criteria for the basic ant colony optimization control parameters. Ant colony optimization algorithm and modified algorithm have been simulated using Cloudsim toolkit package. Experimental results showed that modified ant colony optimization outperformed the ant colony optimization algorithm.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - A. Tawfeek Medhat
AU  - El-Sisi Ashraf
AU  - E. keshk Arabi
AU  - A. Torkey Fawzy
PY  - 2013/11
DA  - 2013/11
TI  - An Ant Algorithm for Cloud Task Scheduling
BT  - Proceedings of the The 1st International Workshop on Cloud Computing and Information Security
PB  - Atlantis Press
SP  - 169
EP  - 172
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccis-13.2013.40
DO  - 10.2991/ccis-13.2013.40
ID  - Medhat2013/11
ER  -