QoS-Aware Web Services Composition Based on HQPSO Algorithm

Web services composition is a new software development paradigm, and it is a key point to achieve serviceoriented computing currently. For meeting the QoS requirements of consumers, this paper presents the QoS calculation rules and formalizes the services composition as the combinatorial optimization problem. In order to solve services composition, a new algorithm based on QPSO algorithm is proposed, which is called Hybrid QPSO algorithm and the correctness, feasibility, and effectiveness of the algorithm are demonstrated using the experiments.

[1]  Yan Ma,et al.  A New Parallel Algorithm of Adaptive QPSO to Solve Constrained Optimization Problems , 2008, 2008 Second International Conference on Genetic and Evolutionary Computing.

[2]  Jerry R. Hobbs,et al.  DAML-S: Semantic Markup for Web Services , 2001, SWWS.

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

[4]  Liu Yang,et al.  PQPSO Algorithm in Multi-Stage Portfolio Optimization System , 2009, 2009 International Workshop on Intelligent Systems and Applications.

[5]  Eric. Newcomer,et al.  Understanding SOA with Web Services , 2004 .

[6]  Manfred Broy,et al.  A formal model of services , 2007, TSEM.

[7]  James A. Fitzsimmons,et al.  Service Management: Operations, Strategy, and Information Technology , 1997 .

[8]  Giuseppe De Giacomo,et al.  Automatic Web Service Composition , 2006, 2006 IEEE International Conference on Services Computing (SCC'06).

[9]  J. A. Fitzsimmons Service Management , 2003 .

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

[11]  Wenbo Xu,et al.  Particle swarm optimization with particles having quantum behavior , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[12]  Stefan Tai,et al.  The next step in Web services , 2003, CACM.

[13]  Bin Zhang,et al.  QoS-Driven Self-Healing Web Service Composition Based on Performance Prediction , 2009, Journal of Computer Science and Technology.

[14]  Emilio Tuosto,et al.  A Logic for Application Level QoS , 2006, QAPL.

[15]  B. Morris Service management: Operations, strategy and information technology, 2nd edition , 1999 .

[16]  Ding Shuai,et al.  Trustworthy Software Evaluation Using Utility Based Evidence Theory , 2009 .

[17]  C. Grönroos Service Management and Marketing: A Customer Relationship Management Approach , 2000 .

[18]  Alfons Kemper,et al.  Adaptive quality of service management for enterprise services , 2008, TWEB.

[19]  Eric. Newcomer,et al.  Understanding SOA with Web Services (Independent Technology Guides) , 2004 .

[20]  Barbara Pernici,et al.  A framework for QoS-based Web service contracting , 2009, TWEB.

[21]  Dmytro Zhovtobryukh,et al.  A Petri Net-based Approach for Automated Goal-Driven Web Service Composition , 2007, Simul..

[22]  Shao Ling Web Service QoS Prediction Approach , 2009 .

[23]  Jiang Wen,et al.  Query Optimization Plan of Web Services Based on Greedy Algorithm , 2008 .

[24]  Amit P. Sheth,et al.  Modeling Quality of Service for Workflows and Web Service Processes , 2002 .

[25]  Liang-Jie Zhang,et al.  Services Computing: Core Enabling Technology of the Modern Services Industry , 2007 .

[26]  Li Zhou,et al.  Web Service QoS Prediction Approach: Web Service QoS Prediction Approach , 2009 .

[27]  Marcel-Catalin Rosu,et al.  A survey of public web services , 2004, WWW Alt. '04.

[28]  Wu Zhaohui,et al.  Automatic Web Service Composition Based on Backward Tree , 2007 .

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

[30]  Farhad Arbab,et al.  QoS-Driven Service Selection and Composition Using Quantitative Constraint Automata , 2009, Fundam. Informaticae.

[31]  Jan Mendling Business Process Execution Language for Web Service (BPEL) , 2006 .