An interval-based congestion control algorithm under varying network conditions

A new IRED (interval random early detection) congestion control algorithm is proposed for network congestion avoidance and resource management. Different to the traditional AQM (active queue management) algorithms, the control parameters of IRED are not configured statically, and is setting as a parameter interval according to the changes of network environment. By the interval parameter design, the IRED alleviates the tuning difficulty of RED (random early detection) and shows a robust performance than RED under varying network conditions. It is proved that the stability and stability margin of the IRED control system can be guaranteed. A systematic design method for the configuration of parameter interval is proposed. Simulation studies show the proposed IRED algorithm achieves a robust control performance in varying network environment, which is superior to the RED and Gentle-RED algorithm.

[1]  Hyunjeong Lee,et al.  Neural network control for TCP network congestion , 2005, Proceedings of the 2005, American Control Conference, 2005..

[2]  Chunming Qiao,et al.  Advances in internet congestion control , 2003, IEEE Communications Surveys & Tutorials.

[3]  Sanjay Lall,et al.  Global Stability Analysis of a Nonlinear Model of Internet Congestion Control With Delay , 2007, IEEE Transactions on Automatic Control.

[4]  Donald F. Towsley,et al.  A control theoretic analysis of RED , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[5]  Yuan Gao,et al.  A variable structure control approach to active queue management for TCP with ECN , 2005, IEEE Transactions on Control Systems Technology.

[6]  R. Srikant,et al.  An adaptive virtual queue (AVQ) algorithm for active queue management , 2004, IEEE/ACM Transactions on Networking.

[7]  Robert Shorten,et al.  Growth Conditions for the Global Stability of High-Speed Communication Networks With a Single Congested Link , 2008, IEEE Transactions on Automatic Control.

[8]  Richard J. La,et al.  Asymptotic Stability of a Rate Control System With Communication Delays , 2007, IEEE Transactions on Automatic Control.

[9]  Lachlan L. H. Andrew,et al.  An Improved Link Model for Window Flow Control and Its Application to FAST TCP , 2009, IEEE Transactions on Automatic Control.

[10]  Kao-Shing Hwang,et al.  Cooperative multiagent congestion control for high-speed networks , 2005, IEEE Trans. Syst. Man Cybern. Part B.

[11]  Oliver W. W. Yang,et al.  Design of Adaptive PI Rate Controller for Best-Effort Traffic in the Internet Based on Phase Margin , 2007, IEEE Transactions on Parallel and Distributed Systems.

[12]  Jin Soo Lee,et al.  Parameter Conditions for Global Stability of FAST TCP , 2008, IEEE Communications Letters.

[13]  Yu-Ping Tian,et al.  A general stability criterion for congestion control with diverse communication delays , 2005, Autom..

[14]  PooGyeon Park,et al.  Improved global stability conditions of the tuning parameter in FAST TCP , 2009, IEEE Commun. Lett..

[15]  Yang Hongyong,et al.  Internet Adaptive Active Queue Management Algorithm , 2006, 2007 Chinese Control Conference.

[16]  R. Srikant,et al.  Exponential-RED: a stabilizing AQM scheme for low- and high-speed TCP protocols , 2005, IEEE/ACM Trans. Netw..

[17]  Steven H. Low,et al.  REM: active queue management , 2001, IEEE Netw..

[18]  Jin Wu,et al.  A Fuzzy-Expert-System-Based Structure for Active Queue Management , 2003, ICIC.