A non-equilibrium analysis and control framework for active queue management

Authors:
Tansu Alpcan;Paul Wang;Prashant G. Mehta;Tamer Başar
Affiliations:
Deutsche Telekom Laboratories, Ernst-Reuter-Platz 7, 10587, Germany;Department of Mechanical Science and Engineering, University of Illinois, 1206 W. Green Street, Urbana IL 61801, United States and Coordinated Science Laboratory, University of Illinois, 1308 West ...;Department of Mechanical Science and Engineering, University of Illinois, 1206 W. Green Street, Urbana IL 61801, United States and Coordinated Science Laboratory, University of Illinois, 1308 West ...;Coordinated Science Laboratory, University of Illinois, 1308 West Main Street, Urbana IL 61801, United States
Venue:
Automatica (Journal of IFAC)
Year:
2008

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Abstract

We present a non-equilibrium analysis and control approach for the Active Queue Management (AQM) problem in communication networks. Using simplified fluid models, we carry out a bifurcation study of the complex dynamic queue behavior to show that non-equilibrium methods are essential for analysis and optimization in the AQM problem. We investigate an ergodic theoretic framework for stochastic modeling of the non-equilibrium behavior in deterministic models and use it to identify parameters of a fluid model from packet level simulations. For computational tractability, we use set-oriented numerical methods to construct finite-dimensional Markov models, including control Markov chains and hidden Markov models. Subsequently, we develop and analyze an example AQM algorithm using a Markov Decision Process (MDP) based control framework. The control scheme developed is optimal with respect to a reward function, defined over the queue size and aggregate flow rate. We implement and simulate our illustrative AQM algorithm in the ns-2 network simulator. The results obtained confirm the theoretical analysis and exhibit promising performance when compared with well-known alternative schemes under persistent non-equilibrium queue behavior.