Information about Congestion Control

This article concerns telecommunications traffic. For road traffic, see traffic congestion.


Congestion control concerns controlling traffic entry into a telecommunications network, so as to avoid congestive collapse by attempting to avoid oversubscription of any of the processing or link capabilities of the intermediate nodes and networks and taking resource reducing steps, such as reducing the rate of sending packets.

Theory of congestion control

The modern theory of congestion control was pioneered by Frank Kelly, who applied microeconomic theory and convex optimization theory to describe how individuals controlling their own rates can interact to achieve an "optimal" network-wide rate allocation

Examples of "optimal" rate allocation are max-min fair allocation and Kelly's suggestion of proportional fair allocation, although many others are possible.

The mathematical expression for optimal rate allocation is as follows. Let be the rate of flow , be the capacity of link , and be 1 if flow uses link and 0 otherwise. Let , and be the corresponding vectors and matrix. Let be an increasing, strictly convex function, called the utility, which measures how much benefit a user obtains by transmitting at rate . The optimal rate allocation then satisfies



such that


The Lagrange dual of this problem decouples, so that each flow sets its own rate, based only on a "price" signalled by the network. Each link capacity imposes a constraint, which gives rise to a Lagrange multiplier, . The sum of these Lagrange multipliers, is the price to which the flow responds.

Congestion control then becomes a distributed optimisation algorithm for solving the above problem. Many current congestion control algorithms can be modelled in this framework, with being either the loss probability or the queueing delay at link .

A major weakness of this model is that it assumes all flows observe the same price, while sliding window flow control causes "burstiness" which causes different flows to observe different loss or delay at a given link.

Classification of congestion control algorithms



There are many ways to classify congestion control algorithms:
  • By the type and amount of feedback received from the network: Loss; delay; single-bit or multi-bit explicit signals
  • By incremental deployability on the current Internet: Only sender needs modification; sender and receiver need modification; only router needs modification; sender, receiver and routers need modification.
  • By the aspect of performance it aims to improve: high bandwidth-delay product networks; lossy links; fairness; advantage to short flows; variable-rate links
  • By the fairness criterion it uses: max-min, proportional, "minimum potential delay"

See Also

External links

Traffic congestion is a condition on any network as use increases and is characterized by slower speeds, longer trip times, and increased queueing. The most common example is for physical use of roads by vehicles.
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A telecommunications network is a of telecommunications links and nodes arranged so that messages may be passed from one part of the network to another over multiple links and through various nodes.
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Congestive collapse (or congestion collapse) is a condition which a packet switched computer network can reach, when little or no useful communication is happening due to congestion.
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data link is the means of connecting one location to another for the purpose of transmitting and receiving data. It can also be an assembly, consisting of parts of two data terminal equipments (DTEs) and the interconnecting data circuit, that is controlled by a link protocol
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Frank Kelly

Professor Frank Kelly at the EPFL, 15 October 2007
Born 28 December 1950

Residence Cambridge
Citizenship British
Field optimisation
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Microeconomics (or price theory) is a branch of economics that studies how individuals, households, and firms make decisions to allocate limited resources,[1] typically in markets where goods or services are being bought and sold.
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Convex optimization is a subfield of mathematical optimization. Given a real vector space together with a convex, real-valued function



defined on a convex subset of , the problem is to find the point in for which the number is smallest, i.e.
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In a proportionally fair scheduling algorithm, the data flows are assigned a data rate that is inversively proportional to its "cost" in terms of resource consumption. For example, a cell phone that is at far distance from the base station will usually achieve lower data rate than
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convex, or concave up, if for any two points x and y in its domain C and any t in [0,1], we have


In other words, a function is convex if and only if its epigraph (the set of points lying on or above the graph) is
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In economics, utility is a measure of the relative satisfaction or desiredness from consumption of goods. Given this measure, one may speak meaningfully of increasing or decreasing utility, and thereby explain economic behavior in terms of attempts to increase one's utility.
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Lagrangian function is defined as



The vectors and are called the dual variables or Lagrange multiplier vectors associated with the problem.
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Lagrange multipliers, named after Joseph Louis Lagrange, is a method for finding the extrema of a function of several variables subject to one or more constraints: it is the basic tool in nonlinear constrained optimization.
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Taxonomy of congestion control refers to grouping congestion control algorithms according to their characteristics.

Example classification

The following is one possible classification according to the following properties:

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congestion avoidance.

TCP Tahoe and Reno

Two such variations are those offered by TCP Tahoe and Reno. TCP specifies a maximum segment size (MSS). The sender maintains a congestion window
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