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Discovering admissible Web services with uncertain QoS

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Abstract

Open and dynamic environments lead to inherent uncertainty of Web service QoS (Quality of Service), and the QoS-aware service selection problem can be looked upon as a decision problem under uncertainty. We use an empirical distribution function to describe the uncertainty of scores obtained from historical transactions. We then propose an approach to discovering the admissible set of services including alternative services that are not dominated by any other alternatives according to the expected utility criterion. Stochastic dominance (SD) rules are used to compare two services with uncertain scores regardless of the distribution form of their uncertain scores. By using the properties of SD rules, an algorithm is developed to reduce the number of SD tests, by which the admissible services can be reported progressively. We prove that the proposed algorithm can be run on partitioned or incremental alternative services. Moreover, we achieve some useful theoretical conclusions for correct pruning of unnecessary calculations and comparisons in each SD test, by which the efficiency of the SD tests can be improved. We make a comprehensive experimental study using real datasets to evaluate the effectiveness, efficiency, and scalability of the proposed algorithm.

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Author information

Authors and Affiliations

  1. Yunnan Provincial Key Laboratory of Computer Technology Application, Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, China

    Xiaodong Fu, Li Liu & Yong Feng

  2. School of Information Science and Engineering, Yunnan University, Kunming, 650091, China

    Kun Yue

  3. Faculty of Management and Economics, Kunming University of Science and Technology, Kunming, 650093, China

    Ping Zou

Authors
  1. Xiaodong Fu
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  2. Kun Yue
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  3. Li Liu
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  4. Ping Zou
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  5. Yong Feng
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Corresponding author

Correspondence to Xiaodong Fu.

Additional information

Xiaodong Fu is a professor in the Faculty of Information Engineering and Automation, Kunming University of Science and Technology, China. He received his MS in Computer Science in 2000 and his PhD in Management Science in 2008. He has authored more than 20 publications on services computing topics. He is a member of the IEEE Computer Society and the ACM. His current research interests include services computing and intelligent decision.

Kun Yue is a professor in the School of Information Science and Engineering, Yunnan University, China. He received his MS in Computer Science from Fudan University, China in 2004, and his PhD in Computer Science from Yunnan University, China in 2009. His research interests include data and knowledge engineering, Web services, and uncertainty in artificial intelligence.

Li Liu is a lecturer in the Faculty of Information Engineering and Automation, Kunming University of Science and Technology, China. She received her PhD in Computer Science from Sun Yat-sen University, China in 2014. Her research interests include cloud computing, Internet-based image processing and analysis.

Ping Zou is a professor and PhD supervisor in the Faculty of Management and Economics, Kunming University of Science and Technology, China. He received his MS in Management Science from Kunming University of Science and Technology in 1988. He has published more than 50 publications on decision making topics. His current research interests include services computing and decision science.

Yong Feng received his PhD in Computer Science from University of Electronic Science and Technology of China in 2011. He is an associate professor in the Faculty of Information Engineering and Automation, Kunming University of Science and Technology, China. His research interests include the Internet of Things and mobile computing.

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Fu, X., Yue, K., Liu, L. et al. Discovering admissible Web services with uncertain QoS. Front. Comput. Sci. 9, 265–279 (2015). https://doi.org/10.1007/s11704-014-4059-9

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  • DOI: https://doi.org/10.1007/s11704-014-4059-9

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