Open Access

ARTICLE

Multi-indicator Active Queue Management Method

Mosleh M. Abualhaj^*, Abdelrahman H. Hussein, Qasem M. Kharma, Qusai Y. Shambour

Faculty of Information, Al-Ahliyya Amman University, Amman, 19328, Jordan

* Corresponding Author: Mosleh M. Abualhaj. Email:

Computer Systems Science and Engineering 2021, 38(2), 251-263. https://doi.org/10.32604/csse.2021.015787

Received 01 December 2020; Accepted 02 January 2021; Issue published 23 April 2021

Abstract

A considerable number of applications are running over IP networks. This increased the contention on the network resource, which ultimately results in congestion. Active queue management (AQM) aims to reduce the serious consequences of network congestion in the router buffer and its negative effects on network performance. AQM methods implement different techniques in accordance with congestion indicators, such as queue length and average queue length. The performance of the network is evaluated using delay, loss, and throughput. The gap between congestion indicators and network performance measurements leads to the decline in network performance. In this study, delay and loss predictions are used as congestion indicators in a novel stochastic approach for AQM. The proposed method estimates the congestion in the router buffer and then uses the indicators to calculate the dropping probability, which is responsible for managing the router buffer. The experimental results, based on two sets of experiments, have shown that the proposed method outperformed the existing benchmark algorithms including RED, ERED and BLUE algorithms. For instance, in the first experiment, the proposed method resides in the third-place in terms of delay when compared to the benchmark algorithms. In addition, the proposed method outperformed the benchmark algorithms in terms of packet loss, packet dropping, and packet retransmission. Overall, the proposed method outperformed the benchmark algorithms because it preserves packet loss while maintaining reasonable queuing delay.

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Keywords

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