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This paper presents an architecture and algorithms for optimizing the performance of Web services. For a given service, session-based admission control is combined with stage-wise request queuing, where the stages represent sub-tasks within sessions. The scheduling of requests is governed by generalized processor sharing. We present a performance model, relying on online estimation of parameters describing client-server interaction. A reward function corresponding to the service provider's objective is maximized using techniques for nonlinear optimization. In a case study, we model and optimize the resource sharing at a Web server hosting an electronic store. The performance advantages of our approach are quantified numerically, and the robustness to parameter estimation errors is assessed by sensitivity analysis.
Carlström et al. (Wed,) studied this question.
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