Web Service Dynamic Selection by the Decomposition of Global QoS Constraints

With the growing number of alternative Web services in the open Web service environment,users have put forward new demands that bind the runtime of Web services,which requires as much short computation time as possible to satisfy user's end-to-end QoS requirements service composition.Therefore,this paper proposes a Web service dynamic selection approach,based on the decomposition of global QoS constraints,WSDSA(Web service dynamic selection approach).The WSDSA uses as adaptive adjustment method(AAM),based on fuzzy logic and adaptive particle swarm optimization algorithm(APSO),to adaptively decompose global QoS constrains to local constraints with the user's preferences,and then WSDSA can obtain the most appropriate composition service with local selection.Performance evaluations show WSDSA is very effective,and is able to reach optimal or near optimal results with a very low time cost,which satisfies the real time and dynamic service selection.

[1]  Thomas Risse,et al.  Combining global optimization with local selection for efficient QoS-aware service composition , 2009, WWW '09.

[2]  Claudia Linnhoff-Popien,et al.  Adaptation of Composite Services in Pervasive Computing Environments , 2007, IEEE International Conference on Pervasive Services.

[3]  Wang Hu,et al.  A Simpler and More Effective Particle Swarm Optimization Algorithm , 2007 .

[4]  Riccardo Poli,et al.  Mean and Variance of the Sampling Distribution of Particle Swarm Optimizers During Stagnation , 2009, IEEE Transactions on Evolutionary Computation.

[5]  Tao Yu,et al.  Efficient algorithms for Web services selection with end-to-end QoS constraints , 2007, TWEB.

[6]  S.N. Singh,et al.  Fuzzy Adaptive Particle Swarm Optimization for Bidding Strategy in Uniform Price Spot Market , 2007, IEEE Transactions on Power Systems.

[7]  Anne H. H. Ngu,et al.  QoS-aware middleware for Web services composition , 2004, IEEE Transactions on Software Engineering.

[8]  R. Eberhart,et al.  Fuzzy adaptive particle swarm optimization , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[9]  M. El-Hawary,et al.  Hybrid Particle Swarm Optimization Approach for Solving the Discrete OPF Problem Considering the Valve Loading Effects , 2007, IEEE Transactions on Power Systems.

[10]  Zhen Li,et al.  Hybrid QoS-aware semantic web service composition strategies , 2008, Science in China Series F: Information Sciences.

[11]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[12]  Wolfgang Kellerer,et al.  Web services selection for distributed composition of multimedia content , 2004, MULTIMEDIA '04.

[13]  Eyhab Al-Masri,et al.  Investigating web services on the world wide web , 2008, WWW.

[14]  Jing Ning,et al.  A Dynamic Web Services Selection Algorithm with QoS Global Optimal in Web Services Composition , 2007 .

[15]  Wu Min,et al.  An Approach to Constructing Web Service Workflow Based on Business Spanning Graph , 2007 .

[16]  Eyhab Al-Masri,et al.  QoS-based Discovery and Ranking of Web Services , 2007, 2007 16th International Conference on Computer Communications and Networks.

[17]  Zhang Cheng,et al.  Genetic Algorithm on Web Services Selection Supporting QoS , 2006 .

[18]  Eyhab Al-Masri,et al.  Discovering the best web service , 2007, WWW '07.

[19]  Hou Zhi-rong,et al.  Particle Swarm Optimization with Adaptive Mutation , 2006 .

[20]  Kyong-Ho Lee,et al.  Fast Quality Driven Selection of Composite Web Services , 2006, 2006 European Conference on Web Services (ECOWS'06).

[21]  Alvin T. S. Chan,et al.  Dynamic QoS Adaptation for Mobile Middleware , 2008, IEEE Transactions on Software Engineering.

[22]  Xuanzhe Liu,et al.  Discovering Homogeneous Web Service Community in the User-Centric Web Environment , 2009, IEEE Transactions on Services Computing.

[23]  Su Sen,et al.  Fuzzy Multi-Attribute Decision Making-Based Algorithm for Semantic Web Service Composition , 2009 .

[24]  Junliang Chen,et al.  DiGA: Population diversity handling genetic algorithm for QoS-aware web services selection , 2007, Comput. Commun..

[25]  Quan Z. Sheng,et al.  Quality driven web services composition , 2003, WWW '03.

[26]  Xiao-hong Chen,et al.  Dynamic services selection algorithm in Web services composition supporting cross-enterprises collaboration , 2009 .

[27]  Shuji Tasaka,et al.  Enhancement of QoE in Audio-Video IP Transmission by Utilizing Tradeoff between Spatial and Temporal Quality for Video Packet Loss , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[28]  H. Rogier,et al.  Beamforming in the Presence of Mutual Coupling Based on Constrained Particle Swarm Optimization , 2009, IEEE Transactions on Antennas and Propagation.

[29]  Danilo Ardagna,et al.  Adaptive Service Composition in Flexible Processes , 2007, IEEE Transactions on Software Engineering.

[30]  George J. Klir,et al.  Fuzzy sets and fuzzy logic - theory and applications , 1995 .