Empirical Characterization of Session–Based Workload and Reliability for Web Servers |
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Authors: | Katerina Goševa-Popstojanova Ajay Deep Singh Sunil Mazimdar Fengbin Li |
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Affiliation: | (1) Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506-6109, USA |
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Abstract: | The growing availability of Internet access has led to significant increase in the use of World Wide Web. If we are to design dependable Web–based systems that deal effectively with the increasing number of clients and highly variable workload, it is important to be able to describe the Web workload and errors accurately. In this paper we focus on the detailed empirical analysis of the session–based workload and reliability based on the data extracted from actual Web logs of eleven Web servers. First, we introduce and rigourously analyze several intra–session and inter–session metrics that collectively describe Web workload in terms of user sessions. Then, we analyze Web error characteristics and estimate the request–based and session–based reliability of Web servers. Finally, we identify the invariants of the Web workload and reliability that apply through all data sets considered. The results presented in this paper show that session–based workload and reliability are better indicators of the users perception of the Web quality than the request–based metrics. |
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Keywords: | Web workload Web error behaviour Web reliability Session-based analysis Heavy-tailed distributions |
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