Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ http://www.cs.unc.ed...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
https://doi.org/10.1109/icdcs....
Article . 2006 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object
Data sources: DBLP
versions View all 2 versions
addClaim

A Loss and Queuing-Delay Controller for Router Buffer Management

Authors: Long Le; Kevin Jeffay; F. Donelson Smith;

A Loss and Queuing-Delay Controller for Router Buffer Management

Abstract

Active queue management (AQM) in routers has been proposed as a solution to some of the scalability issues associated with TCP’s pure end-to-end approach to congestion control. However, beyond congestion control, controlling queues in routers is important because unstable router queues can cause poor application performance. Existing AQM schemes explicitly try to control router queues by probabilistically dropping (or marking) packets. We argue that while controlling router queues is important, this control needs to be tempered by a consideration of the overall lossrate at the router. Solely attempting to control queue length can induce loss-rates that have as negative an effect on application and network performance as the large queues that existing AQM schemes were trying to avoid. Thus controlling queue length without regard to loss-rate can be counterproductive. In this work we demonstrate that by jointly controlling queue length and loss-rate, both network and application performance are improved. We present a novel AQM design that attempts to simultaneously optimize queue length and loss-rate. Our algorithm, called loss and queuing delay control (LQD), is a control theoretic scheme that explicitly treats loss-rate as a control parameter. LQD is shown to provide stable control analytically and is evaluated empirically by comparing its performance against other control theoretic AQM designs (PI and REM). The results of evaluation in a laboratory testbed under realistic traffic mixes and loads show that LQD results in lower overall loss rates and that applications see lower average queue lengths than with PI or REM.

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    1
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average