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Task Scheduling Based on Ant Colony Optimization in Cloud Environment.
- 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]
- Subjects :
- SCHEDULING
CLOUD computing
ALGORITHMS
HEURISTIC algorithms
PHEROMONES
Subjects
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