Wavelet-Domain Statistics of Packet Switching Networks Near Traffic Congestion

Authors:
Pietro Liò;Anna T. Lawniczak;Shengkun Xie;Jiaying Xu
Affiliations:
The Computer Laboratory, University of Cambridge, Cambridge, UK CB3 0FD;Department of Mathematics and Statistics, University of Guelph, Guelph, Canada Ont N1G 2W1;Department of Mathematics and Statistics, University of Guelph, Guelph, Canada Ont N1G 2W1;Department of Mathematics and Statistics, University of Guelph, Guelph, Canada Ont N1G 2W1
Venue:
Bio-Inspired Computing and Communication
Year:
2008

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Abstract

Recent theoretical and applied works have demonstrated the appropriateness of wavelets for analysing signals containing non- stationarity, unsteadiness, self-similarity, and non-Markovity. We applied wavelets to study packet traffic in a packet switching network model, focusing on the spectral properties of packet traffic near phase transition (critical point) from free flow to congestion, and considered different dynamic & static routing metrics. We show that "wavelet power spectra"and variance are important estimators of the changes occurring with source load increasing from sub-critical, through critical, to super-critical and it depends on the routing algorithm.