A smith predictor-based PI-controller for active queue management

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

11 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)4293-4300
Journal / PublicationIEICE Transactions on Communications
VolumeE88-B
Issue number11
Publication statusPublished - Nov 2005

Abstract

Congestion control in the Internet consists of two main components: the TCP Additive-Increase Multiplicative-Decrease (AIMD) mechanism on sending windows implemented by end-users, and the Active Queue Management (AQM) scheme implemented in the routers which improves the effectiveness of congestion control. TCP connection is regarded as a feedback control system. Comparably, AQM is classified as a flow controller. There are several kinds of time delays in the network, such as propagation delay, queuing delay in the buffer of the router, etc. The time delays cause degradation of performance and instability of the network. A Smith Predictor is commonly used in feedback control of plants with significant time delays to implement effective compensation. In this paper, a Smith Predictor-based PI-controller for AQM (SPPA) is proposed, which uses a TCP reference model and an average Round-Trip Time (RTT) to reduce unfavorable effects of time delays in TCP networks. The drop probability is calculated by a Proportional-Integral (PI) controller based on the prediction error. When a mismatch exists in between the actual model of the TCP process and the reference model employed by the SPPA, we demonstrate conditions under which the network is stable. The performance, robustness and effectiveness of the proposed SPPA are all evaluated using simulations. The performance of the SPPA is compared with some typical AQMs, such as the Adaptive RED, the PI-controller, and the Proportional-Differential (PD) controller. Copyright © 2005 The Institute of Electronics, Information and Communication Engineers.

Research Area(s)

  • Active queue management, Congestion control, PI-controller, Smith Predictor