• DocumentCode
    1535452
  • Title

    An Analytic Throughput Model for TCP NewReno

  • Author

    Parvez, Nadim ; Mahanti, Anirban ; Williamson, Carey

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Calgary, Calgary, AB, Canada
  • Volume
    18
  • Issue
    2
  • fYear
    2010
  • fDate
    4/1/2010 12:00:00 AM
  • Firstpage
    448
  • Lastpage
    461
  • Abstract
    This paper develops a simple and accurate stochastic model for the steady-state throughput of a TCP NewReno bulk data transfer as a function of round-trip time and loss behavior. Our model builds upon extensive prior work on TCP Reno throughput models but differs from these prior works in three key aspects. First, our model introduces an analytical characterization of the TCP NewReno fast recovery algorithm. Second, our model incorporates an accurate formulation of NewReno´s timeout behavior. Third, our model is formulated using a flexible two-parameter loss model that can better represent the diverse packet loss scenarios encountered by TCP on the Internet. We validated our model by conducting a large number of simulations using the ns-2 simulator and by conducting emulation and Internet experiments using a NewReno implementation in the BSD TCP/IP protocol stack. The main findings from the experiments are: 1) the proposed model accurately predicts the steady-state throughput for TCP NewReno bulk data transfers under a wide range of network conditions; 2) TCP NewReno significantly outperforms TCP Reno in many of the scenarios considered; and 3) using existing TCP Reno models to estimate TCP NewReno throughput may introduce significant errors.
  • Keywords
    Internet; transport protocols; BSD TCP/IP protocol; Internet; TCP NewReno bulk data transfer; ns-2 simulator; packet loss; round-trip time; steady-state throughput; timeout behavior; two-parameter loss model; ns-2; Analytical modeling; Transmission Control Protocol (TCP); simulation;
  • fLanguage
    English
  • Journal_Title
    Networking, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6692
  • Type

    jour

  • DOI
    10.1109/TNET.2009.2030889
  • Filename
    5308283