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A Stochastic Programming Approach for QoS-Aware Service Composition

Wolfram Wiesemann, Ronald Hochreiter & Daniel Kuhn

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abstract We formulate the service composition problem as a multi-objective stochastic program which simultaneously optimizes the following quality of service (QoS) parameters: workflow duration, service invocation costs, availability, and reliability. All of these quality measures are modelled as decision-dependent random variables. Our model minimizes the average value-at-risk (AVaR) of the workflow duration and costs while imposing constraints on the workflow availability and reliability. AVaR is a popular risk measure in decision theory which quantifies the expected shortfall below some percentile of a loss distribution. By replacingthe random durations and costs with their expected values, our risk-aware model reduces to the nominal problem formulation prevalent in literature. We argue that this nominal model can lead to overly risky decisions. Finally, we report on the scalability properties of our model.
   
type conference paper (English)
   
keywords Stochastic Programming, Web Service Composition, Quality of Service, Average Value-at-Risk
   
name of conference CCgrid 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (Lyon)
date of conference 19-5-2008
page(s) 226-233
publisher IEEE Computer Society (Los Alamitos)
ISBN 978-0-7695-3156-4
review external review
   
citation Wiesemann, W., Hochreiter, R., & Kuhn, D. (2008). A Stochastic Programming Approach for QoS-Aware Service Composition. In , pp.226-233. Los Alamitos: IEEE Computer Society. - ISBN 978-0-7695-3156-4.