QoS-Based Dynamic Web Service Composition with Ant Colony Optimization

Service-oriented architecture (SOA) provides a scalable and flexible framework for service composition. Service composition algorithms play an important role in selecting services from different providers to reach desirable QoS levels according to the performance requirements of composite services, and improve customer satisfaction. This paper proposes a novel QoS-based dynamic service composition technique for web services with Ant Colony Optimization (ACO) in an optimization approach. The novelty of this work lies with our multi-objective optimal-path selection modeling for QoS-based dynamic web service composition and a new version of ACO algorithm that is proposed to solve this multi-objective optimization problem. The experiments show that the new version of ACO algorithm is very efficient in solving such a problem.

[1]  Liu Qinghua,et al.  A Global QoS Optimizing Web Services Selection Algorithm Based on MOACO for Dynamic Web Service Composition , 2009, 2009 International Forum on Information Technology and Applications.

[2]  Günter Rudolph,et al.  Convergence analysis of canonical genetic algorithms , 1994, IEEE Trans. Neural Networks.

[3]  Ian C. Parmee,et al.  The Ant Colony Metaphor for Searching Continuous Design Spaces , 1995, Evolutionary Computing, AISB Workshop.

[4]  Marco Dorigo,et al.  Optimization, Learning and Natural Algorithms , 1992 .

[5]  Jana Koehler,et al.  Web Service Composition - Current Solutions and Open Problems , 2003 .

[6]  Shuanyu Dong,et al.  A QoS Driven Web Service Composition Method Based on ESGA (Elitist Selection Genetic Algorithm) with an Improved Initial Population Selection Strategy , 2009 .

[7]  M. Marchese,et al.  An ant colony optimization method for generalized TSP problem , 2008 .

[8]  Heiko Ludwig,et al.  Web Service Level Agreement (WSLA) Language Specification , 2003 .

[9]  Hwa-Young Jeong,et al.  Best Web Service Selection Based on the Decision Making Between QoS Criteria of Service , 2005, ICESS.

[10]  Yushun Fan,et al.  QoS-Aware Web Service Selection by a Synthetic Weight , 2007, Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007).

[11]  Marco Dorigo,et al.  AntNet: Distributed Stigmergetic Control for Communications Networks , 1998, J. Artif. Intell. Res..

[12]  Jun-Liang Chen,et al.  On the Dynamic Ant Colony Algorithm Optimization Based on Multi-pheromones , 2008, Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008).

[13]  Gary B. Lamont,et al.  Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.

[14]  Huaimin Wang,et al.  Quality driven Web services selection , 2005, IEEE International Conference on e-Business Engineering (ICEBE'05).

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

[16]  Pierre Borne,et al.  Ant systems & Local Search Optimization for flexible Job Shop Scheduling Production , 2007, Int. J. Comput. Commun. Control.

[17]  Maria Luisa Villani,et al.  An approach for QoS-aware service composition based on genetic algorithms , 2005, GECCO '05.

[18]  Arthur H. M. ter Hofstede,et al.  What's in a Service? , 2002, Distributed and Parallel Databases.

[19]  Deren Chen,et al.  Objective Function Analysis for QoS-AwareWeb Service Composition , 2006, 2006 IEEE International Conference on e-Business Engineering (ICEBE'06).

[20]  Maria Luisa Villani,et al.  A Lightweight Approach for QoS–Aware Service Composition , 2006 .

[21]  John H. Miller,et al.  Complex adaptive systems - an introduction to computational models of social life , 2009, Princeton studies in complexity.

[22]  Stephen J. H. Yang,et al.  An optimal QoS-based Web service selection scheme , 2009, Inf. Sci..

[23]  Ralf Steinmetz,et al.  Heuristics for QoS-aware Web Service Composition , 2006, 2006 IEEE International Conference on Web Services (ICWS'06).

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