Energy-Efficient Multi-Job Scheduling Model for Cloud Computing and Its Genetic Algorithm
Joint Authors
Wang, Yuping
Wang, Xiaoli
Zhu, Hai
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-02-08
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
For the problem that the energy efficiency of the cloud computing data center is low, from the point of view of the energy efficiency of the servers, we propose a new energy-efficient multi-job scheduling model based on Google’s massive data processing framework.
To solve this model, we design a practical encoding and decoding method for the individuals and construct an overall energy efficiency function of the servers as the fitness value of each individual.
Meanwhile, in order to accelerate the convergent speed of our algorithm and enhance its searching ability, a local search operator is introduced.
Finally, the experiments show that the proposed algorithm is effective and efficient.
American Psychological Association (APA)
Wang, Xiaoli& Wang, Yuping& Zhu, Hai. 2012. Energy-Efficient Multi-Job Scheduling Model for Cloud Computing and Its Genetic Algorithm. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-1029632
Modern Language Association (MLA)
Wang, Xiaoli…[et al.]. Energy-Efficient Multi-Job Scheduling Model for Cloud Computing and Its Genetic Algorithm. Mathematical Problems in Engineering No. 2012 (2012), pp.1-16.
https://search.emarefa.net/detail/BIM-1029632
American Medical Association (AMA)
Wang, Xiaoli& Wang, Yuping& Zhu, Hai. Energy-Efficient Multi-Job Scheduling Model for Cloud Computing and Its Genetic Algorithm. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-1029632
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1029632