The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 32-672
Full Name: Minghui Wu
Position: Associate Professor
Age: ON
Sex: Male
Address: Dept. of Computer, Zhejiang University City College, No 51, HuzhouJie, Hangzhou, Zhejiang, 310015
Country: CHINA
Tel: +86-571-88284308
Tel prefix:
Fax: +86-571-88015567
E-mail address: minghuiwu@cs.zju.edu.cn
Other E-mails: mhwu@zucc.edu.cn
Title of the Paper: An Global Optimization Approach for Large-scale QoS-driven Web Services Composition
Authors as they appear in the Paper: Minghui Wu, Xianghui Xiong, Canghong Jin, Jing Ying
Email addresses of all the authors: minghuiwu@cs.zju.edu.cn, mseengine@zju.edu.cn, keithzju@188.com, yingj@zucc.edu.cn
Number of paper pages: 10
Abstract: One of the aims of SOA is to compose atomic Web services into a powerful composite service. QoS based selection approaches are used to choose the best solution among candidate services with the same functionality. Due to the increasing scale of the candidate services and demands for real-time in some specific application domains, the rapid convergent algorithm for large-scale Web service composition is especially important, but rare work has been done to solve the problem. This paper describes the Web services composition model and constructs the web service selection mathematical model. According to these models, service composition problem can be considered as Single-objective multi-constraints optimization problem. We propose a new algorithm named GAELS (Genetic Algorithm Embedded Local Searching), which uses the strategies of enhanced initial population and mutation with local searching, to speed up the convergence. Finally, the in-depth experimental results sh!
ow that the GAELS algorithm can get the non-inferior solution more quickly and more adaptively than simple genetic algorithm to large-scale Web service composition.
Keywords: SOA; Web services composition; QoS global optimal; Genetic algorithm; Local searching
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