On Control Parameter Tuning for Active Queue Management Mechanisms using Multivariate Analysis

On Control Parameters Tuning for Active Queue Management Mechanisms using Multivariate Analysis

In recent years, AQM (Active Queue Management) mechanisms, which support the end-to-end congestion control mechanism of TCP by performing congestion control at a router, have been actively studied by many researchers. AQM mechanisms usually have several control parameters, and their effectiveness depends on a setting of those control parameters. Therefore, issues on parameter tuning of several ...

Multivariate Analysis for Performance Evaluation of Active Queue Management Mechanisms in the Internet

AQM (Active Queue Management) mechanism, which performs congestion control at a router for assisting the end-to-end congestion control mechanism of TCP, has been actively studied by many researchers. For instance, RED (Random Early Detection) is a representative AQM mechanism, which drops arriving packets with a probability being proportional to its average queue length. The RED router has four...

An Improvement over Random Early Detection Algorithm: A Self-Tuning Approach

Random Early Detection (RED) is one of the most commonly used Active Queue Management (AQM) algorithms that is recommended by IETF for deployment in the network. Although RED provides low average queuing delay and high throughput at the same time, but effectiveness of RED is highly sensitive to the RED parameters setting. As network condition varies largely, setting RED's parameters with fixed ...

PI Stabilization for Congestion Control of AQM Routers with Tuning Parameter Optimization

On Tuning of Red Parameters

Random Early Detection (RED) [1] is a widely deployed active queue management scheme in packetswitched networks. Although RED can improve packet loss rates, its performance depends severely on the tuning of its operating parameters. To alleviate the problem of parameter dependence, we propose an algorithm to adaptively vary the queue weight wq in conjunction with the maximum packet dropping pro...

A New Self-tuning Active Queue Management Algorithm Based on Adaptive Control

Most Active Queue Management (AQM) algorithms based on control theory have difficulty in obtaining desirable performance once the network conditions or the traffic patterns change out of the presumed ones they are designed for. To address these problems, a new self-tuning AQM algorithm called STR is proposed in this paper. STR has the ability of keeping minimum variance between the instantaneou...