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Conference object . 2017
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https://doi.org/10.1109/smc.20...
Article . 2017 . Peer-reviewed
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Conference object
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Hamiltonian theory applied to ameliorate the complexity of tcp network congestion control

Authors: Wang, Kun; Jing, Yuanwei; Zhang, Siying; Dimirovski, Georgi M.;

Hamiltonian theory applied to ameliorate the complexity of tcp network congestion control

Abstract

An active queue management controller based on Hamiltonian energy theory for a class of nonlinear TCP network congestion system in the p resence of uncertain parameters and unknown external disturbances is derived. The restriction of inequality assumption is eliminated by introducing the MiniMax methods into dissipation Hamilton system. Sufficient conditions for the existence of MiniMax controller under circumstances the network system is attacked with maximum impact disturbance has been derived via Lyapunov stability theory. Furthermore, the nonlinear uncertainties presence i.s successfully ameliorated by employing a parameter projection mechanism. Simulation experiments have demonstrated this energy based control strategy ameliorates the pertinent control complexity and is considerably more effective in improving both transient stability and robustness.

Country
Turkey
Related Organizations
Keywords

Adptive Control, TCP Highspeed Networks, Hamiltonian Energy Theory, MiniMax Control, AQM Technology, Congestion Control

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    popularity
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    influence
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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!
2
Average
Average
Average
Green