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Task Scheduling Based on Ant Colony Optimization in Cloud Environment.

Authors :
Qiang Guo
Source :
AIP Conference Proceedings; 2017, Vol. 1834 Issue 1, p1-11, 11p, 1 Diagram, 2 Charts, 3 Graphs
Publication Year :
2017

Abstract

In order to optimize the task scheduling strategy in cloud environment, we propose a cloud computing task scheduling algorithm based on ant colony algorithm. The main goal of this algorithm is to minimize the makespan and the total cost of the tasks, while making the system load more balanced. In this paper, we establish the objective function of the makespan and costs of the tasks, define the load balance function. Meanwhile, we also improve the initialization of the pheromone, the heuristic function and the pheromone update method in the ant colony algorithm. Then, some experiments were carried out on the Cloudsim platform, and the results were compared with algorithms of ACO and Min-Min. The results shows that the algorithm is more efficient than the other two algorithms in makespan, costs and system load balancing. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
1834
Issue :
1
Database :
Complementary Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
122804473
Full Text :
https://doi.org/10.1063/1.4981635