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Entropy Based Discriminators for P2P Teletraffic Characterization

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Neural Information Processing (ICONIP 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7063))

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Abstract

Characterization of P2P traffic is an essential step to develop workload models towards capacity planning and cyberthreat countermeasure over P2P networks. In this paper, we present a new scheme for monitoring and characterizing File-Sharing P2P (FSP2P) applications. Featured by both lightweightness and high prediction accuracy, the proposed scheme supports performance tuning between monitoring cost and the system response time, and is adaptable to network environments with different specifications.

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Ban, T., Guo, S., Eto, M., Inoue, D., Nakao, K. (2011). Entropy Based Discriminators for P2P Teletraffic Characterization. In: Lu, BL., Zhang, L., Kwok, J. (eds) Neural Information Processing. ICONIP 2011. Lecture Notes in Computer Science, vol 7063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24958-7_3

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  • DOI: https://doi.org/10.1007/978-3-642-24958-7_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24957-0

  • Online ISBN: 978-3-642-24958-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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