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Robust Multi-criteria Service Composition in Information Systems

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  • René Ramacher
  • Lars Mönch

Abstract

Service compositions are used to implement business processes in a variety of application domains. A quality of service (QoS)-aware selection of the service to be composed involves multiple, usually conflicting and possibly uncertain QoS attributes. A multi-criteria solution approach is desired to generate a set of alternative service selections. In addition, the uncertainty of QoS-attributes is neglected in existing solution approaches. Hence, the need for service reconfigurations is imposed to avoid the violation of QoS restrictions. The researched problem is NP-hard. This article presents a heuristic multi-criteria service selection approach that is designed to determine a Pareto frontier of alternative service selections in a reasonable amount of time. Taking into account the uncertainty of response times, the obtained service selections are robust with respect to the constrained execution time. The proposed solution approach is based on the Non-dominated Sorting Genetic Algorithm (NSGA)-II extended by heuristics that exploit problem specific characteristics of the QoS-aware service selection. The applicability of the solution approach is demonstrated by a simulation study. Copyright Springer Fachmedien Wiesbaden 2014

Suggested Citation

  • René Ramacher & Lars Mönch, 2014. "Robust Multi-criteria Service Composition in Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(3), pages 141-151, June.
    • Handle: RePEc:spr:binfse:v:6:y:2014:i:3:p:141-151
    DOI: 10.1007/s12599-014-0325-5
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    References listed on IDEAS

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    1. Pisinger, David, 1995. "A minimal algorithm for the multiple-choice knapsack problem," European Journal of Operational Research, Elsevier, vol. 83(2), pages 394-410, June.
    2. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    3. Scholl, Armin, 2000. "Robuste Planung und Optimierung: Grundlagen, Konzepte und Methoden; experimentelle Untersuchungen," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 9373, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
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