DocumentCode :
694395
Title :
Research on cloud computing schedule based on improved hybrid PSO
Author :
Yang Xiaoguang ; Chen Tingbin ; Zhang Qisong
Author_Institution :
Inf. Technol. & Bus. Manage., Dalian Neusoft Univ. of Inf., Dalian, China
fYear :
2013
fDate :
12-13 Oct. 2013
Firstpage :
388
Lastpage :
391
Abstract :
In the cloud computing environment, one of the hot spot of researches in cloud computing is how to accomplish the service request in numerous running tasks. This paper puts forward an improved hybrid particle swarm optimization, making the particle swarm algorithm as the main level algorithm and the improved ant colony algorithm as the secondary level algorithm. The algorithm uses the main level algorithm to generate the initial pheromone distribution and utilizes the secondary algorithm that max-min ant colony algorithm to obtain the best solution. Finally, the availability and advantage of the proposed algorithm can be tested through the simulation experiment.
Keywords :
ant colony optimisation; cloud computing; minimax techniques; particle swarm optimisation; scheduling; cloud computing environment; cloud computing schedule; hybrid PSO; hybrid particle swarm optimization; max-min ant colony algorithm; particle swarm algorithm; pheromone distribution; secondary algorithm; secondary level algorithm; Algorithm design and analysis; Cloud computing; Information technology; Optimization; Particle swarm optimization; Processor scheduling; Scheduling; cloud computing; improved PSO algorithm; task scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on
Conference_Location :
Dalian
Type :
conf
DOI :
10.1109/ICCSNT.2013.6967136
Filename :
6967136
Link To Document :
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