Paper
8 August 2003 Modeling and design of admission control mechanisms for web servers using nonlinear control theory
Mikael Andersson, Maria Kihl, Anders Robertsson
Author Affiliations +
Abstract
Web sites are exposed to high rates of incoming requests. Since web sites are sensitive to overload, admission control mechanisms are often implemented. The purpose of such a mechanism is to prevent requests from entering the web server during high loads. This paper presents how admission control mechanisms can be designed and implemented with a combination of queueing theory and control theory. Since web servers behave non-linear and stochastic, queueing theory can be used for web server modelling. However, there are no mathematical tools in queueing theory to use when designing admission control mechanisms. Instead, control theory contains the needed mathematical tools. By analysing queueing systems with control theoretic methods, good admission control mechanisms can be designed for web server systems. In this paper we model an Apache web server as a GI/G/1-system. Then, we use control theory to design a PI-controller, commonly used in automatic control, for the web server. In the paper we describe the design of the controller and also how it can be implemented in a real system. The controller has been implemented and tested together with the Apache web server. The server was placed in a laboratory network together with a traffic generator which was used to represent client requests. Measurements in the laboratory setup show how robust the implemented controller is, and how it correspond to the results from the theoretical analysis.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mikael Andersson, Maria Kihl, and Anders Robertsson "Modeling and design of admission control mechanisms for web servers using nonlinear control theory", Proc. SPIE 5244, Performance and Control of Next-Generation Communications Networks, (8 August 2003); https://doi.org/10.1117/12.509281
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CITATIONS
Cited by 19 scholarly publications and 9 patents.
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KEYWORDS
Control systems

Systems modeling

Stochastic processes

Nonlinear control

Automatic control

Computing systems

Mathematical modeling

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