1. Copyright © 2005 Department of Computer Science CPSC 641 Winter 20111 Self-Similar Network Traffic The original paper on network traffic self-similarity appeared at the 1993 ACM SIGCOMM Conference Authors: Will Leland, Murad Taqqu, Walter Willinger, and Daniel Wilson (Leland et al. 1993) Studied Ethernet LAN traffic Extended version appeared in IEEE/ACM Transactions on Networking, Vol. 2, No. 1, February 1994 One of the landmark papers of the 1990’s Highly regarded, influential, one of the most cited papers in the networking literature

2. Copyright © 2005 Department of Computer Science CPSC 641 Winter 20112 Main Contributions Identified presence of self-similarity property in aggregate Ethernet traffic Defined methodology for testing for the presence of self-similarity –autocorrelation function –variance-time plot –R/S statistic –periodogram (power spectrum) Proposed explanations/models for SS

3. Copyright © 2005 Department of Computer Science CPSC 641 Winter 20113 Measurement Study Detailed measurement study of very lengthy Ethernet packet traces, with high resolution timer, and lots of storage space One of the traces presented in their paper is a 27.5 hour trace Over 20 million packets

4. Copyright © 2005 Department of Computer Science CPSC 641 Winter 20114 Data Analysis Detailed statistical analysis: –aggregation, autocorrelation, R/S analysis, variance- time plot, periodograms, Whittle’s estimator, maximum likelihood... Very rigourous: confidence intervals, sophisticated statistical tests, sound methodology,... A wonderful paper to read (over and over)

5. Copyright © 2005 Department of Computer Science CPSC 641 Winter 20115 Main Results Aggregate Ethernet LAN traffic is self-similar Burstiness across many time scales Hurst parameter 0.7 < H < 0.9 H is larger when network utilization is higher (e.g., 0.9 when U = 15%) Self-similarity present on all LANs tested

6. Copyright © 2005 Department of Computer Science CPSC 641 Winter 20116 Conclusions Self-similarity is present in aggregate Ethernet LAN traffic Traffic does not aggregate well at all Law of large numbers may not hold! Poisson models (or Markovian models of any sort) do not capture reality at all Important to consider self-similar traffic