[Nrg-l] Next week's NRG

Niky Riga inki at cs.bu.edu
Mon Nov 8 15:20:09 EST 2004

Just a reminder that the NRG will start in about 40 minutes at MCS135.

CU all there,

On Fri, 5 Nov 2004, Niky Riga wrote:

> Hi,
> This Monday, November 8th, at MCS135 from 4-5, Vijay will present
> the following paper at the NRG meeting.                                                                                                                         
> "A pragmatic approach to dealing with high-variability in network
> measurements", by Walter Willinger, David Alderson and Lun Li.
> (http://delivery.acm.org/10.1145/1030000/1028800/p88-willinger.pdf?key1=1028800&key2=1892869901&coll=GUIDE&dl=GUIDE&CFID=30540751&CFTOKEN=35177039)
> This paper appeared in this year's IMC.
> Please, read also this paper, which complement some of the ideas of the
> former.
> Evidence for long-tailed distributions in the Internet Allen B. Downey
> (http://www.icir.org/vern/imw-2001/imw2001-papers/35.pdf)
>  The abstract of the talk follows.
> Niky
> ---------------------------------------------------------------------------                                                                                                                       
> The Internet is teeming with high variability phenomena, from measured IP
> flow sizes to aspects of inferred router-level connectivity, but there
> still exists considerable debate about how best to deal with this
> encountered high variability and model it. While one popular approach
> favors modeling highly variable event sizes with conventional, finite
> variance distributions such as lognormal or Weibull distributions,
> Mandelbrot has argued for the last 40 years that there are compelling
> mathematical, statistical, and practical reasons for why infinite variance
> distributions are natural candidates for capturing the essence behind high
> variability phenomena. In this paper, we elaborate on Mandelbrot's
> arguments and present a methodology that often allows for a clear
> distinction between the two approaches. In particular, by requiring the
> resulting models to be resilient to ambiguities (i.e., robust to
> real-world deficiencies in the underlying network measurements) and
> internally self-consistent (i.e., insensitive with respect the duration,
> location, or time of the data collection), we provide a rigorous framework
> for a qualitative assessment of the observed high variability. We apply
> the proposed framework to assess previously reported findings about
> measured Internet traffic and inferred router- and AS-level
> connectivity. In the process, we also discuss what our approach has to say
> about recent discussions concerning network traffic being Poisson or
> self-similar and router-level or AS-level connectivity graphs of the
> Internet being scale-free or not.
> ------------------------------------------------------------------------------                                                                                                                       
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>                 -- Wm. Shakespeare
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