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.