Presentation 2005-01-25
Congestion Control in the Network Router Introducing a Nonlinear Characteristics
Yusuke NISHIUCHI, Tetsushi UETA, Chikara OHTA,
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Abstract(in English) The congestion state of the packet in a network will get worse if the state is left as it is. Active Queue Management (AQM) predicts a congestion and rejects packet in the network router. One of the most fundamental AQM is Random Early Detection (RED). RED predicts the buffer of router and rejects packets by probability. If RED parameters suitable for environment of a network is set up, throughput and fairness of a network are improved. However, since the environment of a network changes dynamically, a setup of a RED parameters is difficult. Packet-dropping probability is determined in a linear probability according to the state of a buffer. In this report, we show that RED improve in quality, if a nonlinear curve substitutes for a linear of probability. Practically, we built the network environment of simulesion where some machines communicated by one machine, and we experiment in TCP connection.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) network router / congestion control / AQM / RED / TCP
Paper # NLP2004-107
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Conference Information
Committee NLP
Conference Date 2005/1/18(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Congestion Control in the Network Router Introducing a Nonlinear Characteristics
Sub Title (in English)
Keyword(1) network router
Keyword(2) congestion control
Keyword(3) AQM
Keyword(4) RED
Keyword(5) TCP
1st Author's Name Yusuke NISHIUCHI
1st Author's Affiliation Graduate Schools of Engineering, Tokushima University()
2nd Author's Name Tetsushi UETA
2nd Author's Affiliation Center for Advanced Information Technology, Tokushima University
3rd Author's Name Chikara OHTA
3rd Author's Affiliation Department of Computer and Systems Engineering, Faculty of Engineering, Kobe University
Date 2005-01-25
Paper # NLP2004-107
Volume (vol) vol.104
Number (no) 584
Page pp.pp.-
#Pages 6
Date of Issue