An Exponential Active Queue Management Method Based on Random Early Detection

Abstract

Congestion is a key topic in computer networks that has been studied extensively by scholars due to its direct impact on a network’s performance. One of the extensively investigated congestion control techniques is random early detection (RED). To sustain RED’s performance to obtain the desired results, scholars usually tune the input parameters, especially the maximum packet dropping probability, into specific value(s). Unfortunately, setting up this parameter into these values leads to good, yet biased, performance results. In this paper, the RED-Exponential Technique (RED_E) is proposed to deal with this issue by dropping arriving packets in an exponential manner without utilizing the maximum packet dropping probability. Simulation tests aiming to contrast E_RED with other Active Queue Management (AQM) methods were conducted using different evaluation performance metrics including mean queue length (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mtext>mql</mml:mtext></mml:math>), throughput (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mi>T</mml:mi></mml:math>), average queuing delay (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mi>D</mml:mi></mml:math>), overflow packet loss probability (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:msub><mml:mrow><mml:mi>P</mml:mi></mml:mrow><mml:mrow><mml:mi>L</mml:mi></mml:mrow></mml:msub></mml:math>), and packet dropping probability (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M5"><mml:msub><mml:mrow><mml:mi>D</mml:mi></mml:mrow><mml:mrow><mml:mi>P</mml:mi></mml:mrow></mml:msub></mml:math>). The reported results showed that E_RED offered a marginally higher satisfactory performance with reference to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M6"><mml:mtext>mql</mml:mtext></mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M7"><mml:mi>D</mml:mi></mml:math> than that found in common AQM methods in cases of heavy congestion. Moreover, RED_E compares well with the considered AQM methods with reference to the above evaluation performance measures using minimum threshold position (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M8"><mml:mi mathvariant="normal">min</mml:mi><mml:mtext> threshold</mml:mtext></mml:math>) at a router buffer.

Topics & Concepts