DocumentCode :
3301503
Title :
QoS Scheduling Algorithm Based on Hybrid Particle Swarm Optimization Strategy for Grid Workflow
Author :
Hu, Chunhua ; Wu, Min ; Liu, Guoping ; Xie, Wen
Author_Institution :
Dept. of Comput. & Electron. Eng., Hunan Bus. Coll., Changsha
fYear :
2007
fDate :
16-18 Aug. 2007
Firstpage :
330
Lastpage :
337
Abstract :
The service oriented grid workflow has been a research focus in grid technology. As an NP complete problem, grid service scheduling is difficult to solve by means of classic algorithms This paper presents an algorithm HPSOA (hybrid particle swarm optimization algorithm) to resolve dynamic Web services selection with QoS global optimal in grid workflow.The essence of the algorithm is that the problem of dynamic Web Service selection with QoS global optimal is transformed into a multi-objective services composition optimization with QoS constraints. The operations of the cross and mutation in genetic algorithm are brought into PSOA (particle swarm optimization algorithm) to form a mix algorithm, which called HPSOA solve the QoS global optimal problem. Theoretical analysis and experimental results indicate the feasibility and efficiency of the algorithm.
Keywords :
Web services; computational complexity; grid computing; particle swarm optimisation; quality of service; scheduling; NP complete problem; QoS constraints; QoS global optimal problem; QoS scheduling; dynamic Web services selection; genetic algorithm; grid service scheduling; grid technology; hybrid particle swarm optimization algorithm; multiobjective services composition optimization; service oriented grid workflow; Algorithm design and analysis; Educational institutions; Genetic algorithms; Grid computing; Information science; Particle swarm optimization; Quality of service; Scheduling algorithm; Web and internet services; Web services; Grid workflow; QoS global optimal; hybrid particle swarm optimization Algorithm (HPSOA); service selection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Grid and Cooperative Computing, 2007. GCC 2007. Sixth International Conference on
Conference_Location :
Los Alamitos, CA
Print_ISBN :
0-7695-2871-6
Type :
conf
DOI :
10.1109/GCC.2007.100
Filename :
4293798
Link To Document :
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