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Integrated Random Early Detection for Congestion Control at the Router Buffer

Ahmad Adel Abu-Shareha*

The World Islamic Sciences and Education University (WISE), Amman, Jordan

* Corresponding Author: Ahmad Adel Abu-Shareha. Email: email

Computer Systems Science and Engineering 2022, 40(2), 719-734. https://doi.org/10.32604/csse.2022.018369

Abstract

This paper proposed an Integrated Random Early Detection (IRED) method that aims to resolve the problems of the queue-based AQM and load-based AQM and gain the benefits of both using indicators from both types. The arrival factor (e.g., arrival rate, queue and capacity) and the departure factors are used to estimate the congestion through two integrated indicators. The utilized indicators are mathematically calculated and integrated to gain unified and coherent congestion indicators. Besides, IRED is built based on a new dropping calculation approach that fits the utilized congestion indicators while maintaining the intended buffer management criteria, avoiding global synchronization and enhancing the performance. The results showed that IRED, compared to RED, BLUE, ERED, FLRED, EnRED and DcRED, decreased packet delay and loss under various network status. Specifically, the results showed that in heavy and moderate traffic, the proposed IRED method outperformed the state-of-the-art methods in loss and delay by 18% and 10.6%, respectively.

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Cite This Article

APA Style
Abu-Shareha, A.A. (2022). Integrated random early detection for congestion control at the router buffer. Computer Systems Science and Engineering, 40(2), 719-734. https://doi.org/10.32604/csse.2022.018369
Vancouver Style
Abu-Shareha AA. Integrated random early detection for congestion control at the router buffer. Comput Syst Sci Eng. 2022;40(2):719-734 https://doi.org/10.32604/csse.2022.018369
IEEE Style
A.A. Abu-Shareha, “Integrated Random Early Detection for Congestion Control at the Router Buffer,” Comput. Syst. Sci. Eng., vol. 40, no. 2, pp. 719-734, 2022. https://doi.org/10.32604/csse.2022.018369



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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