Preference-aware QoS evaluation for cloud web service composition based on artificial neural networks

Authors:
Xuyun Zhang;Wanchun Dou
Affiliations:
State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China and Department of Computer Science and Technology, Nanjing University, Nanjing, China;State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China and Department of Computer Science and Technology, Nanjing University, Nanjing, China
Venue:
WISM'10 Proceedings of the 2010 international conference on Web information systems and mining
Year:
2010

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Abstract

Since QoS properties play an increasingly important role during the procedure of web service composition in Cloud environment, they have obtained great interests in both research community and IT domain. Yet evaluating the comprehensive QoS values of composite services in accord with the consumers' preferences is still a significant but challenging problem due to the subjectivity of consumers. Since reflecting preference by the explicit weights assigned for each criterion is quite arduous, this paper proposes a global QoS-driven evaluation method based on artificial neural networks, aiming at facilitating the web service composition without preference weights. As well as this, a prototype composition system is developed to bolster the execution of proposed approach.