Markov Model Based Congestion Control for TCP

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Markov Model Based Congestion Control for TCP
The Random Early Detection (RED) scheme for congestion control in TCP is well known over a decade. Due to a number of control parameters in RED, it cannot make acceptable packet-dropping decision, especially, under heavy network load and high delay to provide high throughput and low packet loss rate. We propose a solution to this problem using Markov chain based decision rule. We modeled the oscillation of the average queue size as a homogeneous Markov chain with three states and simulated the system using the network simulator software NS-2. The simulations show that the proposed scheme successfully estimates the maximum packet dropping probability for Random Early Detection. It detects the congestion very early and adjusts the packet-dropping probability so that RED can make wise packet-dropping decisions. Simulation results show that the proposed scheme provides improved connection throughput and reduced packet loss rate.
Shan Suthaharan
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2004
Where ANSS
Authors Shan Suthaharan
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