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The QoS-Based Multi-Objective Optimization Algorithm of the Composite Service Execution Path(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2012年03期
Page:
125-133
Research Field:
计算机科学
Publishing date:

Info

Title:
The QoS-Based Multi-Objective Optimization Algorithm of the Composite Service Execution Path
Author(s):
Li Ying1; 2; Tong Weiqing1; Kang Chaofeng3; Zhi Xiaoli1
1.School of Computer Engineering and Science,Shanghai University,Shanghai 200072,China
Keywords:
QoS; multi-objective optimization; Pareto set; Ant Colony System; virtual abstract service
PACS:
TP393.09
DOI:
-
Abstract:
In this paper，after discussing the limitations of heuristic algorithm using for composite service execution path optimization，an optimization algorithm of Ant Colony System based on Ant Colony Algorithm is proposed． The algorithm regards the optimization problem as the shortest path solving problem of ant foraging from nest to food． In order to overcome the lack of Ant Colony System only using to solved sequential organization path，a concept of virtual abstract service was put forward innovatively to shield the different path structures，then local and global updating rules had been redesigned and the constrained QoS parameters were also into the definition of parameter． Finally，through simulation and comparing with basic Ant Colony Algorithm experimental verified the usability and superiority of the algorithm．

References:

［1］ Li Y，Hu Y，Tong W Q， et al． The service template composition method based on separation of concerns［C］/ / Proc of the 2010 IEEE International Conference on Progress in Informatics and Computing． Shanghai，2010: 1 057-1 059．
［2］ Zitzler E，Laumanns M，Thiele L． SPEA2: Improving the strength Pareto evolutionary algorithm［C］/ / Giannakoglou K， Tsahalis D T，Périaux J，et al． Evolutionary Methods for Design，Optimization and Control with Applications to Industrial Problems． Berlin: Springer-Verlag，2002: 95-100．
［3］ Coello C A，Pulido G T，Lechuga M S． Handing multiple objectives with particle swarm optimization［J］． IEEE Transaction on Evolutionary Computations，2004，8 ( 3) : 256-279．
［4］ Wang Y，Dai G P，Hou Y R． Dynamic methods of Trust-Aware composite service selection ［J］． Chinese Journal of Computers， 2009， 32( 8) : 1 668-1 675．［5］ Peng X M，He Y X，Zhu B J． Application of Ant Colony Algorithm in Web services composition［J］． Computing Engineering， 2009，35( 10) : 182-188．
［6］ Li S Y． Ant Colony Algorithms With Applications［M］． Harbin: Harbin Institute of Technology Press，2004．
［7］ Nahrstedt K，Wichadakul D，Xu D． Distributed QoS compilation and runtime instantiation［C］/ / Proceedings of the 8th IEEE/IFIP International Workshop on Quality of Service． Pittsburgh，2000: 198-207．
［8］ Martin M，Chopard B，Albuquerque P． Formation of an ant cemetery: Swarm intelligence of statistical accident［J］． Future Generation Computer Systems，2002，18: 893-901．
［9］ Duan H B． Ant Colony Algorithms: Theory and Applications［M］． Beijing: Science Press，2005．
［10］ Zeng L Z，Benatallah B． QoS-aware middleware for Web services composition［J］． IEEE Transactions on Software Engineering， 2004，30( 5) : 311-327．［11］ Liu S L，Liu Y X，Zhang F，et al． A dynamic Web services selection algorithm with QoS global optimal in Web services composition［J］． Journal of Software，2007，18( 3) : 646-656．
［12］ 刘波，杨路明，雷刚跃． 融合粒子群与蚁群算法优化XML 群体智能搜索［J］． 计算机研究与发展， 2008，45( 8) : 1 371- 1 378．
［13］ Dai Y，Yang L，Zhang B，et al． QoS for composite Web services and optimizing［J］． Chinese Journal of Computers， 2006， 29( 7) : 1 167-1 178．

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Last Update: 2013-03-11