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Journal ArticleDOI

Random early detection gateways for congestion avoidance

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TLDR
Red gateways are designed to accompany a transport-layer congestion control protocol such as TCP and have no bias against bursty traffic and avoids the global synchronization of many connections decreasing their window at the same time.
Abstract
The authors present random early detection (RED) gateways for congestion avoidance in packet-switched networks. The gateway detects incipient congestion by computing the average queue size. The gateway could notify connections of congestion either by dropping packets arriving at the gateway or by setting a bit in packet headers. When the average queue size exceeds a present threshold, the gateway drops or marks each arriving packet with a certain probability, where the exact probability is a function of the average queue size. RED gateways keep the average queue size low while allowing occasional bursts of packets in the queue. During congestion, the probability that the gateway notifies a particular connection to reduce its window is roughly proportional to that connection's share of the bandwidth through the gateway. RED gateways are designed to accompany a transport-layer congestion control protocol such as TCP. The RED gateway has no bias against bursty traffic and avoids the global synchronization of many connections decreasing their window at the same time. Simulations of a TCP/IP network are used to illustrate the performance of RED gateways. >

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Citations
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Recommendations on Queue Management and Congestion Avoidance in the Internet

TL;DR: This memo presents a strong recommendation for testing, standardization, and widespread deployment of active queue management in routers, to improve the performance of today's Internet.
Journal ArticleDOI

Layering as Optimization Decomposition: A Mathematical Theory of Network Architectures

TL;DR: A survey of the recent efforts towards a systematic understanding of layering as optimization decomposition can be found in this paper, where the overall communication network is modeled by a generalized network utility maximization problem, each layer corresponds to a decomposed subproblem, and the interfaces among layers are quantified as functions of the optimization variables coordinating the subproblems.
Journal ArticleDOI

Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED

TL;DR: This paper uses jump process driven Stochastic Differential Equations to model the interactions of a set of TCP flows and Active Queue Management routers in a network setting and presents a critical analysis of the RED algorithm.
Proceedings ArticleDOI

Receiver-driven layered multicast

TL;DR: The RLM protocol is described, its performance is evaluated with a preliminary simulation study that characterizes user-perceived quality by assessing loss rates over multiple time scales, and the implementation of a software-based Internet video codec is discussed.
Proceedings ArticleDOI

End-to-end Internet packet dynamics

TL;DR: The prevalence of unusual network events such as out-of-order delivery and packet corruption are characterized and a robust receiver-based algorithm for estimating "bottleneck bandwidth" is discussed that addresses deficiencies discovered in techniques based on "packet pair".
References
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Book ChapterDOI

Probability Inequalities for sums of Bounded Random Variables

TL;DR: In this article, upper bounds for the probability that the sum S of n independent random variables exceeds its mean ES by a positive number nt are derived for certain sums of dependent random variables such as U statistics.
Journal ArticleDOI

Congestion avoidance and control

TL;DR: The measurements and the reports of beta testers suggest that the final product is fairly good at dealing with congested conditions on the Internet, and an algorithm recently developed by Phil Karn of Bell Communications Research is described in a soon-to-be-published RFC.
Book

Forecasting, Structural Time Series Models and the Kalman Filter

TL;DR: In this article, the Kalman filter and state space models were used for univariate structural time series models to estimate, predict, and smoothen the univariate time series model.
Posted Content

Forecasting, Structural Time Series Models and the Kalman Filter

TL;DR: In this paper, the authors provide a unified and comprehensive theory of structural time series models, including a detailed treatment of the Kalman filter for modeling economic and social time series, and address the special problems which the treatment of such series poses.
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