[Nrg-l] Next week's NRG

Niky Riga inki at cs.bu.edu
Fri Nov 5 14:44:22 EST 2004


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

---------------------------------------------------------------------------                                                                                                                       
ABSTRACT
                                                                                                                       
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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