Abstract

Based on the proportionally fair scheme that Kelly proposed to solve the optimization problems for utility function in networks, and in order to improve the congestion control performance for the queue in router, the linear and terminal sliding active queue management (AQM) algorithms are designed. Especially in the ter-minal sliding AQM algorithm, a special nonlinear terminal sliding surface is designed in order to force queue length to reach the desired value in finite time. The upper bound of the time is also obtained. Simulation re-sults demonstrate that the proposed congestion algorithm enables the system be better transient and stable performance. At the same time, the robustness is guaranteed.

Highlights

  • Active Queue Management (AQM), as a class of packet dropping/marking mechanism in the router queue, has been recently proposed in order to convey congestion notification early enough to the senders, so that the senders are able to reduce the transmission rates before the queue overflows and any sustained packet loss occurs [1]

  • There are three typical kinds of AQM algorithms: One is heuristic algorithms, such as RED (Random Early Detection) [2], BLUE [3]; One is the utility function optimal model based on economics, like REM (Random Exponential Marking) [4], AVQ (Adaptive Virtual Queue) [5]; The other one is based on the sourcing and queuing dynamic model, as PI [6] and VRC (Virtual Rate Control) [7]

  • We combine the Kelly’s optimization scheme and the sliding mode control algorithm to analyze the convergence of the queue

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Summary

Introduction

Active Queue Management (AQM), as a class of packet dropping/marking mechanism in the router queue, has been recently proposed in order to convey congestion notification early enough to the senders, so that the senders are able to reduce the transmission rates before the queue overflows and any sustained packet loss occurs [1]. There are three typical kinds of AQM algorithms: One is heuristic algorithms, such as RED (Random Early Detection) [2], BLUE [3]; One is the utility function optimal model based on economics, like REM (Random Exponential Marking) [4], AVQ (Adaptive Virtual Queue) [5]; The other one is based on the sourcing and queuing dynamic model, as PI [6] and VRC (Virtual Rate Control) [7] The advantage of the latter two algorithms is that the design of controller is based on explicit model, so the stability analysis and parameters modulation can be given theoretically. The terminal sliding mode control (TSMC) has been developed [13, 14], which can guarantee the finite reaching time to the sliding surface from initial states and the finite reaching time to the equilibrium point

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