摘要
针对云计算平台的新特征,对原有自适应遗传算法进行改进,提出了一种基于用户满意度的遗传算法(consumer satisfaction genetic algorithm,CSGA)。该算法在保证用户公平性的前提下,将任务调度到输入数据所在的计算节点以减少网络传输开销,并以缩短总任务的完成时间及提高用户满意度为目标优化算法性能。通过仿真实验对比分析CSGA与AGA算法,实验结果表明该算法在响应时间、公平性和用户满意度方面优于AGA算法,更加适应云计算环境。
According to the new characteristics of cloud computing platform, this paper proposed an improved genetic algorithm called CSGA. The algorithm under the promise of guarantee consumer fairness, CSGA scheduled tasks to the node with data block of this tasks in order to reduce data translation cost, which aimed to shorten all the task completion time and tried hard to improve the consumer satisfaction. Through the simulation analysis of CSGA and adaptive genetic algorithm （AGA）, it shows that CSGA outperforms previous genetic algorithms in term of the job response time and fairness and consumer satisfaction, and the CSGA is better adapted to the cloud computing environment.
出处
《计算机应用研究》
CSCD
北大核心
2014年第1期85-88,共4页
Application Research of Computers
基金
国家自然科学基金资助项目(60863003
61063042)
新疆维吾尔自治区自然科学基金资助项目(2011211A011)
关键词
云计算
任务调度算法
遗传算法
公平性
用户满意度
cloud computing task scheduling algorithm genetic algorithm fairness consumer satisfaction
