2002Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIERequires access

Guidelines for optimizing multilevel ECN using fluid-flow-based TCP model

P.-F. Quet, Sriram Chellappan, Arjan Durresi, Mukundan Sridharan, Hitay Özbay, Raj Jain

Open publisher page 6 citations

Abstract

Congestion avoidance on today's Internet is mainly provided by the combination of the TCP protocol and Active Queue Management (AQM) schemes such as the de facto standard RED (Random Early Detection). When used with ECN (Explicit Congestion Notification), these algorithms can be modeled as a feedback control system in which the feedback information is carried on a single bit. A modification of this scheme called MECN was proposed, where the marking information is carried using 2 bits. MECN conveys more accurate feedback about the network congestion to the source than the current 1-bit ECN. The TCP source reaction was modified so that it takes advantage of the extra information about congestion and adapts faster to the changing congestion scenario leading to a smoother decrease in the sending rates of the sources upon congestion detection and consequently resulting in an increase in the router's throughput. A linearized fluid flow model already developed for ECN is extended to our case. Using control theoretic tools we justify the performance obtained in using the MECN scheme and give guidelines for optimizing its parameters. We use ns simulations to illustrate the performance improvement from the point of better throughput and low level of oscillations in the queue.

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What this paper is about

Congestion avoidance on today's Internet is mainly provided by the combination of the TCP protocol and Active Queue Management (AQM) schemes such as the de facto standard RED (Random Early Detection). When used with ECN (Explicit Congestion Notification), these algorithms can be modeled as a feedback control system in which the feedback information is carried on a single bit. A modification of this scheme called MECN was proposed, where the marking information is carried using 2 bits. MECN conveys more accurate feedback about the network congestion to the source than the current 1-bit ECN. The TCP source reaction was modified so that it takes advantage of the extra information about congestion and adapts faster to the changing congestion scenario leading to a smoother decrease in the sending rates of the sources upon congestion detection and consequently resulting in an increase in the router's throughput. A linearized fluid flow model already developed for ECN is extended to our case. Using control theoretic tools we justify the performance obtained in using the MECN scheme and give guidelines for optimizing its parameters. We use ns simulations to illustrate the performance improvement from the point of better throughput and low level of oscillations in the queue.

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Available abstract

Congestion avoidance on today's Internet is mainly provided by the combination of the TCP protocol and Active Queue Management (AQM) schemes such as the de facto standard RED (Random Early Detection). When used with ECN (Explicit Congestion Notification), these algorithms can be modeled as a feedback control system in which the feedback information is carried on a single bit. A modification of this scheme called MECN was proposed, where the marking information is carried using 2 bits. MECN conveys more accurate feedback about the network congestion to the source than the current 1-bit ECN. The TCP source reaction was modified so that it takes advantage of the extra information about congestion and adapts faster to the changing congestion scenario leading to a smoother decrease in the sending rates of the sources upon congestion detection and consequently resulting in an increase in the router's throughput. A linearized fluid flow model already developed for ECN is extended to our case. Using control theoretic tools we justify the performance obtained in using the MECN scheme and give guidelines for optimizing its parameters. We use ns simulations to illustrate the performance improvement from the point of better throughput and low level of oscillations in the queue.

Key concepts: Active queue management, Explicit Congestion Notification, Random early detection, Network congestion, Computer science, Computer network, Router, Throughput

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