Cloud Service Scheduling Algorithm Research and Optimization
Joint Authors
Cui, Hongyan
Liu, Xiaofei
Yu, Tao
Zhang, Honggang
Fang, Yajun
Xia, Zongguo
Source
Security and Communication Networks
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-01-11
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Information Technology and Computer Science
Abstract EN
We propose a cloud service scheduling model that is referred to as the Task Scheduling System (TSS).
In the user module, the process time of each task is in accordance with a general distribution.
In the task scheduling module, we take a weighted sum of makespan and flowtime as the objective function and use an Ant Colony Optimization (ACO) and a Genetic Algorithm (GA) to solve the problem of cloud task scheduling.
Simulation results show that the convergence speed and output performance of our Genetic Algorithm-Chaos Ant Colony Optimization (GA-CACO) are optimal.
American Psychological Association (APA)
Cui, Hongyan& Liu, Xiaofei& Yu, Tao& Zhang, Honggang& Fang, Yajun& Xia, Zongguo. 2017. Cloud Service Scheduling Algorithm Research and Optimization. Security and Communication Networks،Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1202823
Modern Language Association (MLA)
Cui, Hongyan…[et al.]. Cloud Service Scheduling Algorithm Research and Optimization. Security and Communication Networks No. 2017 (2017), pp.1-7.
https://search.emarefa.net/detail/BIM-1202823
American Medical Association (AMA)
Cui, Hongyan& Liu, Xiaofei& Yu, Tao& Zhang, Honggang& Fang, Yajun& Xia, Zongguo. Cloud Service Scheduling Algorithm Research and Optimization. Security and Communication Networks. 2017. Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1202823
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202823
