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Exponential Convergence Flow Control Model for Congestion Control

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Intelligent Computing (ICIC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4113))

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Abstract

Recently, many new flow control mechanisms derived from classic Kelly model are proposed to solve network congestion problem. They perform well in stability, fairness or robustness. However, most of their convergence rates are linear since in classic Kelly model, link price is only positive. In addition, some need to introduce extra packet header to get price information. This paper presents a novel flow control model based on Kelly model in which the link price can be negative to improve the convergence rate. Further, The proposed model uses two bits of ECN field to feed back price instead of introducing new packet header data. Thus it can implement flow control scheme achieving exponential convergence in traditional TCP/IP datagram format. NS2 simulation results show that our model can keep fairness and asymptotic stability with more rapid convergence rate.

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© 2006 Springer-Verlag Berlin Heidelberg

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Liu, W., Yi, J., Zhao, D., Wen, J.T. (2006). Exponential Convergence Flow Control Model for Congestion Control. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_100

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  • DOI: https://doi.org/10.1007/11816157_100

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37271-4

  • Online ISBN: 978-3-540-37273-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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