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Performance Analysis for E-Business: Impact of Long Range Dependence

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Abstract

We consider an e-business web-server system where the network traffic exhibits self-similarity. We demonstrate that traditional techniques are unsuitable for predicting the network performance under such traffic conditions. Instead, we propose and demonstrate a novel decomposition approximation technique that helps predict delays more accurately and thus is better suited for capacity planning and network design when compared to traditional queueing network analyzers. We also consider several strategies for mitigating the effect of self-similarity, and conclude that admission control holds the greatest potential for improving service. We provide an approximation technique for computing the admission control parameter values. Numerical results and suggestions for future work are discussed.

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Authors and Affiliations

  1. Department of Industrial Engineering, The Pennsylvania State University, 310 Leonhard Building, University Park, PA, 16802

    Natarajan Gautam

  2. Operations Management Department, Leonard N. Stern School of Business, New York University, NY, 10012

    Sridhar Seshadri

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  1. Natarajan Gautam
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  2. Sridhar Seshadri
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Gautam, N., Seshadri, S. Performance Analysis for E-Business: Impact of Long Range Dependence. Electronic Commerce Research 2, 233–253 (2002). https://doi.org/10.1023/A:1016006515344

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