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DOI: 10.14569/IJACSA.2019.0100310
PDF

Stabilizing Average Queue Length in Active Queue Management Method

Author 1: Mahmoud Baklizi

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 3, 2019.

  • Abstract and Keywords
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Abstract: This paper proposes the Stabilized (DGRED) method for congestion detection at the router buffer. This method aims to stabilize the average queue length between allocated minthre_shold and doublemaxthre_shold positions to increase the network performance. The SDGRED method is simulated and compared with Gentle Random Early Detection (GRED) and Dynamic GRED active queue management methods. This comparison is built on different important measures, such as dropping probability, throughput, average delay, packet loss, and mean queue length for packets. The evaluation aims to identify which method presents better simulation performance measurement results when non-congestion or congestion situations occur at the router buffers in congestion control. The results show that at high packet arrival probability, the proposed algorithm helps provide lesser queue length values, delayed time, and packet loss compared with current methods. Furthermore, SDGRED generates adequate throughput at high packet arrival probability.

Keywords: Congestion control methods; GRED; dynamic GRED; random; simulation; active queue management method

Mahmoud Baklizi, “Stabilizing Average Queue Length in Active Queue Management Method” International Journal of Advanced Computer Science and Applications(IJACSA), 10(3), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100310

@article{Baklizi2019,
title = {Stabilizing Average Queue Length in Active Queue Management Method},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100310},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100310},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {3},
author = {Mahmoud Baklizi}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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