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 :
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