DocumentCode
3768441
Title
Scheduling strategy based on genetic algorithm for Cloud computer energy optimization
Author
Huang Zhen Jin; Lu Yang; Ouyang Hao
Author_Institution
School of computer and information, Hefei University of Technology, China
fYear
2015
Firstpage
516
Lastpage
519
Abstract
During the processing of Cloud platform it will generate a large amount of energy consumption. so how to improve energy efficiency become increasingly important. This paper presents a scheduling strategy which is based on the genetic algorithm for Cloud computing energy optimal. First, we adopt queuing network for system modeling and prove that the energy consumption of Cloud computing system is determined by the task scheduling probability. In order to obtain minimum energy consumption, genetic algorithms based on optimal reservation selection is use to optimize the dispatch probability. Simulation results show that this method is feasible to optimize energy consumption of cloud computing system.
Keywords
"Energy efficiency","Cloud computing","Indium phosphide","III-V semiconductor materials","Sociology","Statistics","Analytical models"
Publisher
ieee
Conference_Titel
Communication Problem-Solving (ICCP), 2015 IEEE International Conference on
Print_ISBN
978-1-4673-6543-7
Type
conf
DOI
10.1109/ICCPS.2015.7454218
Filename
7454218
Link To Document