Abstract
This paper proposes an auto regressive moving average (ARMAX)-based adaptive control methodology to prevent congestion in high-speed asynchronous transfer mode (ATM) networks. Adaptive controller is developed to control traffic where sources adjust their transmission rates in response to the feedback information from the network switches. Specifically, the buffer dynamics at a given switch is modeled as a nonlinear discrete-time system and an ARMAX controller is designed so as to predict the explicit values of the transmission rates of the sources so as to prevent congestion. Tuning methods are provided for the unknown coefficients of the ARMAX model to estimate the unpredictable and statistically fluctuating network traffic. Mathematical analysis is given to demonstrate the stability of the closed-loop system so that a desired quality of service (QoS) can be guaranteed. The QoS is defined in terms of cell loss ratio (CLR), transmission delay and buffer utilization. We derive design rules mathematically for selecting the parameters of the ARMAX algorithm such that the desired performance is guaranteed during congestion and potential tradeoffs are shown. Simulation results are provided to justify the theoretical conclusions for multiple source/single switch scenarios using both ON/OFF and MPEG data. The performance of the proposed congestion control scheme is also evaluated in the presence of feedback delays for robustness considerations. Finally, comparison studies are also included to show the effectiveness of the proposed method over conventional rate-based and thresholding techniques during simulated congestion. The proposed method is shown to be applicable for designing routing algorithms, transmission links and so on.
Recommended Citation
S. Jagannathan and J. Talluri, "Adaptive Predictive Congestion Control of High-speed ATM Networks," IEEE Transactions on Broadcasting, vol. 48, no. 2, pp. 129 - 139, Institute of Electrical and Electronics Engineers, Jun 2002.
The definitive version is available at https://doi.org/10.1109/TBC.2002.1021279
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Keywords and Phrases
ATM networks; Predictive congestion control; Quality of service; Ttraffic rate control
International Standard Serial Number (ISSN)
0018-9316
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jun 2002
Comments
National Science Foundation, Grant ECS 0296191