DocumentCode :
1971757
Title :
Genetic Algorithm for Context-Aware Service Composition Based on Context Space Model
Author :
Zhichao Zhang ; Shaoqiu Zheng ; Weiping Li ; Ying Tan ; Zhonghai Wu ; Wei Tan
Author_Institution :
Sch. of Electron. Eng. & Comput. Sci., Peking Univ., Beijing, China
fYear :
2013
fDate :
June 28 2013-July 3 2013
Firstpage :
605
Lastpage :
606
Abstract :
The emergence of Web services has changed the Internet a lot, and greatly facilitated the development of service based software systems. How to select appropriate services and compose them according to given context to satisfy a user´s requirement is a big challenge. This paper proposes a novel Genetic Algorithm (GA) method to synthesis web services in a context-aware environment. We first present a context space model to illustrate both contexts and services in a formal way, we utilize GA to compose context-aware services according to users´ preference. We transform the problem of service composition to a multi-objective optimization problem. To resolve the conflict and dependencies among services in GA process, we propose a service similarity tree (SST) model to measure the similarity between services. Finally, we design a simulation experiment to evaluate our method. The experiment result shows that our method is a promising one to solve service composition problem in a context-aware environment.
Keywords :
Web services; genetic algorithms; ubiquitous computing; GA process; Internet; SST model; Web services; context space model; context-aware service composition; genetic algorithm; multiobjective optimization problem; service based software systems; service composition problem; service similarity measure; service similarity tree; user preference; Biological cells; Context; Context modeling; Educational institutions; Genetic algorithms; Silicon; Web services; Context aware; Genetic Algorithm; Web Services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Services (ICWS), 2013 IEEE 20th International Conference on
Conference_Location :
Santa Clara, CA
Print_ISBN :
978-0-7695-5025-1
Type :
conf
DOI :
10.1109/ICWS.2013.94
Filename :
6649631
Link To Document :
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