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THE TITLE OF YOUR PAPER. Your Name Communication Networks Laboratory http://www.ensc.sfu.ca/research/cnl School of Engineering Science Simon Fraser University. Roadmap. Motivation for packet loss analysis Sources of packet loss in the Internet Packet loss characterization Methodology

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the title of your paper

THE TITLE OF YOUR PAPER

Your Name

Communication Networks Laboratory

http://www.ensc.sfu.ca/research/cnl

School of Engineering Science

Simon Fraser University

roadmap
Roadmap
  • Motivation for packet loss analysis
  • Sources of packet loss in the Internet
  • Packet loss characterization
  • Methodology
  • Simulation scenarios
  • Simulation results
  • Conclusions and future work

Simulation and analysis: paper title

ns 2 network simulator
ns-2 network simulator
  • Collaborative project among Xerox PARC, LBL, and UCB (http://www.isi.edu/nsnam/ns/)
  • Discrete event network simulator
  • Provides support for various:
    • network protocols
    • topologies
    • traffic generators

Simulation and analysis: paper title

comparison of simulation data with the gilbert models
Comparison of simulation datawith the Gilbert models
  • ulp = 0.15
  • clp = 0.45
  • Gilbert model fits the simulation data for small loss episodes
  • Gilbert model underestimates the probability of having longer loss episodes

Simulation run with 100 UDP sources and buffer size of 50 KB (9.2 msec). The loss from source number 50 is observed.

Simulation and analysis: paper title

analysis of packet loss on multiple time scales
Analysis of packet loss on multiple time scales
  • What is time scale?
  • Wavelet analysis of packet loss

UDP scenario

TCP scenario

Simulation and analysis: paper title

conclusions
Conclusions
  • UDP transfers:
  • lengthier packet loss episodes have large contribution, which indicates that UDP packet loss is highly bursty
  • contribution of packet loss episodes decreases approximately geometrically with increase of the length of packet loss episode

Simulation and analysis: paper title

references
References
  • K. Park and W. Willinger, “Self-similar network traffic: an overview,” in Self-similar Network Traffic and Performance Evaluation, K. Park and W. Willinger, Eds. New York: Wiley, 2000, pp. 1–38.
  • D. Veitch and P. Abry, “A wavelet-based joint estimator of the parameters of long-range dependence,” IEEE Trans. Information Theory, vol. 45, no. 3, pp. 878–897, Apr. 1999.
  • V. Jacobson, “Congestion avoidance and control,” in Proc. ACM SIGCOMM '88 Symposium on Communications Architectures and Protocols, Stanford, CA, USA, Aug. 1988, pp. 314–329.
  • J. C. Bolot, “End-to-end packet delay and loss behavior in the Internet,” in Proc. ACM SIGCOMM '93 Conference on Communications Architectures, Protocols and Applications, San Francisco, CA, USA, Sept. 1993, pp. 289–298.
  • M. Yajnik, S. Moon, J. Kurose, and D. Towsley, “Measurement and modeling of the temporal dependence in packet loss,” in Proc. IEEE INFOCOM, New York, NY, USA, Mar. 1999, pp. 345–352.

Simulation and analysis: paper title