ROBUST CONGESTION CONTROL IN HIGH SPEED COMMUNICATION NETWORKS: A MODEL PREDICTIVE CONTROL APPROACH
Hua O. Wang*,** Yongru Gu* Huajing Fang**
* Laboratory for Intelligent and Nonlinear Control (LINC) Department of Electrical and Computer Engineering Duke University, Durham, NC 27708-0291 USA
** Center for Nonlinear and Complex Systems Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074, China

In this paper, the design of explicit rate-based congestion control in high speed communication networks is considered. At a bottleneck node, there are multiple best-effort sources competing with other high priority cross traffic sources. The goal of congestion control is to achieve high link utilization, low packet loss, low delay, and fairness among the best-effort sources. In this paper, the high priority traffic is described by an autoregressive integrated moving average (ARIMA) process. To deal with the propagation delays associated with the best-effort sources, model predictive control, particularly, generalized predictive control, techniques are proposed to solve the congestion problem here. It is demonstrated that the proposed controller performs well and is robust to delay uncertainties. In addition, in a multiple-nodes configuration, the controller provides max-min fairness.
Keywords: Communication control applications, Model-based control, Predictive control, Communication networks, Time delay, Robustness
Session slot T-We-M16: New Challenges for Controller Design/Area code 2a : Control Design

|