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Titolo:
Traffic modeling, prediction, and congestion control for high-speed networks: A fuzzy AR approach
Autore:
Chen, BS; Peng, SC; Wang, KC;
Indirizzi:
Natl Tsing Hua Univ, Dept Elect Engn, Hsinchu 30043, Taiwan Natl Tsing HuaUniv Hsinchu Taiwan 30043 ect Engn, Hsinchu 30043, Taiwan Natl Huwei Inst Technol, Dept Elect Engn, Huwei 632, Yunlin, Taiwan Natl Huwei Inst Technol Huwei Yunlin Taiwan 632 Huwei 632, Yunlin, Taiwan
Titolo Testata:
IEEE TRANSACTIONS ON FUZZY SYSTEMS
fascicolo: 5, volume: 8, anno: 2000,
pagine: 491 - 508
SICI:
1063-6706(200010)8:5<491:TMPACC>2.0.ZU;2-5
Fonte:
ISI
Lingua:
ENG
Soggetto:
CALL ADMISSION CONTROL; LONG-RANGE DEPENDENCE; BIT-RATE VIDEO; ATM NETWORKS; TCP CONNECTIONS; MULTIPLEXER; SYSTEMS; VOICE;
Keywords:
cell loss rate; fuzzy-AR approach; quality of service (QoS); traffic prediction;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
41
Recensione:
Indirizzi per estratti:
Indirizzo: Chen, BS Natl Tsing Hua Univ, Dept Elect Engn, Hsinchu 30043, Taiwan Natl Tsing Hua Univ Hsinchu Taiwan 30043 Hsinchu 30043, Taiwan
Citazione:
B.S. Chen et al., "Traffic modeling, prediction, and congestion control for high-speed networks: A fuzzy AR approach", IEEE FUZ SY, 8(5), 2000, pp. 491-508

Abstract

In general, high-speed network traffic is a complex, nonlinear, nonstationary process and is significantly affected by immeasurable parameters and variables. Thus, a precise model of this process becomes increasingly difficult as the complexity of the process increases. Recently, fuzzy modeling hasbeen found to be a powerful method to effectively describe a real, complex, and unknown process with nonlinear and time-varying properties. In this study, a fuzzy autoregressive (fuzzy-AR) model is proposed to describe the traffic characteristics of high-speed networks. The fuzzy-AR model approximates a nonlinear time-variant process with a combination of several linear local AR processes using a fuzzy clustering method. We propose that the use of this fuzzy-AR model has greater potential for congestion control of packet network traffic. The parameter estimation problem in fuzzy-AR modeling is treated by a clustering algorithm developed from actual traffic data in high-speed networks. Based on adaptive AR-prediction model and queueing theory, a simple congestion control scheme is proposed to provide an efficient traffic management for high-speed networks. Finally, using the actual ethernet-LAN packet traffic data, several examples are given to demonstrate the validity of this proposed method for high-speed network traffic control.

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Documento generato il 09/07/20 alle ore 20:56:02