Analytical Modeling and Comparison of AQM-Based Congestion Control Mechanisms

Active Queue Management (AQM) is an effective mechanism to support end-to-end traffic congestion control in modern high-speed networks. The selection of different dropping functions and threshold values required for this scheme plays a critical role on its effectiveness. This paper proposes an analytical performance model for AQM using various dropping functions. The model uses a well-known Markov-Modulated Poisson Process (MMPP) to capture traffic burstiness and correlations. Extensive analytical results have indicated that exponential dropping function is a good choice for AQM to support efficient congestion control.

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