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Using Load Transformations to Predict the Impact of Packet Fragmentation and Losses on Markovian Arrival Processes

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 5055))

Abstract

Load transformation can be used to derive valid load models for secondary loads in computer networks, as they can be observed at lower layer interfaces in protocol stacks. In this paper we apply the technique of load transformation onto load represented by BMAP (Batch Markov Arrival Process) models and choose as concrete transformations the following two practically relevant classes of load transforming processes in packet-switched networks: “Fragmentation” and “Losses of Packets”. Comparing the analytical characteristics of load after transformation with corresponding load predictions based on load transformation by simulation, we are able to show that realistic modeling is feasible for both classes of transformations considered. We also illustrate the usefulness of the analytical models elaborated by deriving a detailed prediction of secondary load characteristics which, in turn, can be used to specifically optimize performance measures (such as network throughput).

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Khalid Al-Begain Armin Heindl Miklós Telek

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Heckmüller, S., Wolfinger, B.E. (2008). Using Load Transformations to Predict the Impact of Packet Fragmentation and Losses on Markovian Arrival Processes. In: Al-Begain, K., Heindl, A., Telek, M. (eds) Analytical and Stochastic Modeling Techniques and Applications. ASMTA 2008. Lecture Notes in Computer Science, vol 5055. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68982-9_3

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  • DOI: https://doi.org/10.1007/978-3-540-68982-9_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68980-5

  • Online ISBN: 978-3-540-68982-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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