Stability of the Internet congestion control with diverse delays

Automatica ◽  
2004 ◽  
Vol 40 (9) ◽  
pp. 1533-1541 ◽  
Author(s):  
Yu-Ping Tian ◽  
Hong-Yong Yang
Keyword(s):  
Congestion Control ◽  
The Internet ◽  
Internet Congestion Control ◽  
Internet Congestion

Generalized TCP-RED dynamical model for Internet congestion control

2020 ◽  
Vol 82 ◽  
pp. 105075
Author(s):  
José M. Amigó ◽  
Guillem Duran ◽  
Angel Giménez ◽  
Oscar Martínez-Bonastre ◽  
José Valero
Keyword(s):  
Congestion Control ◽  
Dynamical Model ◽  
Internet Congestion Control ◽  
Internet Congestion

PI-PD Controller for Adaptive and Robust Active Queue Management for Internet Congestion Control

SIMULATION ◽  
2005 ◽  
Vol 81 (6) ◽  
pp. 437-459 ◽  
Author(s):  
Seungwan Ryu ◽  
Byunghan Ryu ◽  
Myoungki Jeong ◽  
Seikwon Park
Keyword(s):  
Congestion Control ◽  
Active Queue Management ◽  
Queue Management ◽  
Pd Controller ◽  
Internet Congestion Control ◽  
Internet Congestion

Digital Bifurcation Analysis of Internet Congestion Control Protocols

2020 ◽  
Vol 30 (13) ◽  
pp. 2030038
Author(s):  
Nikola Beneš ◽  
Luboš Brim ◽  
Samuel Pastva ◽  
David Šafránek
Keyword(s):  
Congestion Control ◽  
Bifurcation Analysis ◽  
Gradient Descent ◽  
Automated Analysis ◽  
Internet Congestion Control ◽  
Integral Feedback ◽  
Internet Congestion ◽  
Control Protocols ◽  
The Stability ◽  
Parameter Dependent

Digital bifurcation analysis is a new algorithmic method for exploring how the behavior of a parameter-dependent discrete system varies with a change in its parameters and, in particular, for the identification of bifurcation points where such variation becomes dramatic. We have developed the method in an analogy with the traditional bifurcation theory and have successfully applied it to models taken from systems biology. In this paper, we report on the application of the digital bifurcation analysis for analyzing the stability of internet congestion control protocols by inspecting their attractor bifurcations. In contrast to the analytical methods, our approach allows fully automated analysis. We compared the robustness of the basic Random Early Drop (RED) approach with four substantially different extensions, namely gentle, adaptive, gradient descent, and integral feedback RED. The basic RED protocol is well known to exhibit unstable behavior when parameters are varied. In the case of adaptive and gradient descent RED protocol, the analysis showed significant improvements in stability, whereas in the results for gentle and integral feedback RED protocols the improvement was negligible. We performed a series of model simulations, the results of which were in accordance with our bifurcation analysis. Based on our results, we can recommend both adaptive and gradient descent RED to improve the robustness of the RED protocol.

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