DocumentCode :
2131627
Title :
An Adaptive Solution for Web Service Composition
Author :
Wang, Hongbing ; Guo, Xiaohui
Author_Institution :
Sch. of Comput. Sci. & Eng., Southeast Univ., Nanjing, China
fYear :
2010
fDate :
5-10 July 2010
Firstpage :
503
Lastpage :
510
Abstract :
Dynamic Web service composition is challenging problem and has been intensively investigated in recent years. Nevertheless, most of existing approaches do not provide satisfactory composition results, especially when confronted with a large scale of services. In this paper, we present a novel algorithm called HRLPLA for composing Web services. The algorithm considers functional properties and QoS properties simultaneously. By using hierarchical reinforcement learning, it can deal with large scales of services and generate efficient service compositions. Moreover, the algorithm is suitable for composing Web services in dynamic environment, as reinforcement learning his highly adaptive. We conducted experimental study to verify the effectiveness and efficiency of our method in dynamic service composition.
Keywords :
Web services; learning (artificial intelligence); HRLPLA; QoS properties; dynamic Web service composition; functional properties; hierarchical reinforcement learning; Artificial intelligence; Heuristic algorithms; Markov processes; Planning; Probabilistic logic; Quality of service; Web services; Hierarchical Reinforcement Learning; MAXQ and Logic of Preference; Web Service Composition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Services (SERVICES-1), 2010 6th World Congress on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4244-8199-6
Electronic_ISBN :
978-0-7695-4129-7
Type :
conf
DOI :
10.1109/SERVICES.2010.20
Filename :
5575463
Link To Document :
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