eprintid: 601
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/06/01
datestamp: 2023-11-09 15:48:44
lastmod: 2023-11-09 15:48:44
status_changed: 2023-11-09 15:22:47
type: conference_item
metadata_visibility: show
creators_name: Dahab, A.Y.
creators_name: Said, A.M.
creators_name: Hasbullah, H.
title: Predicting traffic bursts using extreme value theory
ispublished: pub
keywords: Bellcore; Block maxima; Domain of attraction; Extreme value theory; Gaussians; Generalized extreme value; Network quality of services; Self-similar; Self-similar input; Shape parameters, Forecasting; Quality of service; Signal analysis; Signal processing; Weibull distribution, Traffic signals
note: cited By 4; Conference of 2009 International Conference on Signal Acquisition and Processing, ICSAP 2009 ; Conference Date: 3 April 2009 Through 5 April 2009; Conference Code:79615
abstract: Traffic Bursts appear to be more pronounced recently and have major consequences for network Quality of Service. We investigate the extreme behavior of bursts and quantify the probabilities of these large bursts. Taking Bellcore internal Ethernet traces as an example, we applied Generalized Extreme Value model over block maxima. The analysis reveals that traffic burst maxima follows GEV model with negative shape parameter. Traffic bursts are in the domain of attraction of Weibull distribution. Our result confirms the conclusion of Norros of storage fed with Gaussian self-similar input. © 2009 IEEE.
date: 2009
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-77949974801&doi=10.1109%2fICSAP.2009.52&partnerID=40&md5=1f4d2d487469029d8b00e2f2cbf4736d
id_number: 10.1109/ICSAP.2009.52
full_text_status: none
publication: 2009 International Conference on Signal Acquisition and Processing, ICSAP 2009
place_of_pub: Kuala Lumpur
pagerange: 229-233
refereed: TRUE
isbn: 9780769535944
citation:   Dahab, A.Y. and Said, A.M. and Hasbullah, H.  (2009) Predicting traffic bursts using extreme value theory.  In: UNSPECIFIED.