A multi-task scheduling method based on ant colony algorithm combined QoS in cloud computing

被引:0
|
作者
机构
[1] Wang, Jianping
[2] Zhu, YanLi
[3] Feng, HongYu
来源
Wang, J. (Xunji2002@163.com) | 1600年 / Advanced Institute of Convergence Information Technology卷 / 04期
关键词
Ant colony optimization - Simulated annealing - Genetic algorithms - Multitasking - Scheduling algorithms - Digital storage;
D O I
10.4156/AISS.vol4.issue11.22
中图分类号
学科分类号
摘要
The huge computing tasks and mass data-storage put forward the greater challenges to multi-task scheduling of cloud computing. Solving the bottleneck of multi-task scheduling based on ant colony algorithm can provide an important way for the performance optimization of cloud computing. In this paper, we put forward a multi-task scheduling method based on ant colony algorithm combined QoS, expound the quantization process of QoS and the mathematical model of ant colony algorithm. After that, the multi-task scheduling process is described in detail. Finally, the algorithm of simulation process is realized on CloudSim. By contrasting with genetic algorithm and simulated annealing algorithm, we know that, the operating efficiency of ant colony algorithm is high relatively. It will achieve the global search of the distributed network through accumulating and updating pheromones.
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