Int J Performability Eng ›› 2017, Vol. 13 ›› Issue (7): 1070-1076.doi: 10.23940/ijpe.17.07.p9.10701076

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Cloud Task Scheduling Algorithm based on Improved Genetic Algorithm

Hu Yao, Xueliang Fu*, Honghui Li, Gaifang Dong, and Jianrong Li   

  1. College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China

Abstract: Cloud computing is a new type of business computing model. It is connected through the network and can obtain various applications, data and IT services. The core of cloud computing is task scheduling, and the application of genetic algorithm (GA) in cloud computing task scheduling is also a hot topic in recent years. In this paper, the "three-stage selection method" and the genetic strategy of "total-division-total" are put forward to improve genetic algorithm. Using simulation experiments in cloud computing simulation software named Cloudsim, the experimental results show that comparing with the simple genetic algorithm (SGA), the improved genetic algorithm (IGA) is better than the simple genetic algorithm on completion time, and it is an effective task scheduling algorithm in cloud computing environment.


Submitted on July 25, 2017; Revised on August 30, 2017; Accepted on September 15, 2017
References: 13