Random early detection-quadratic linear: an enhanced active queue management algorithm
Autor: | Samuuel Oluwatosin Hassan, Vivian Ogochukwu Nwaocha, Adewole Usman Rufai, Tola John Odule, Theophilus Aniemeka Enem, Lukman Adebayo Ogundele, Suleiman Abu Usman |
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Rok vydání: | 2022 |
Předmět: | |
Zdroj: | Bulletin of Electrical Engineering and Informatics. 11:2262-2272 |
ISSN: | 2302-9285 2089-3191 |
DOI: | 10.11591/eei.v11i4.3875 |
Popis: | This paper identifies the lone linear drop function for computing the dropping probability between certain queue threshold values as a major weakness for the random early detection (RED) algorithm as it leads to large delay and queue instability. To address this concern, we propose an enhanced RED-based algorithm called random early detection-quadratic linear (referred to as “RED-QL”) active queue management (AQM) which leveraged the benefit of a quadratic packet drop function for a light-to moderate traffic load conditions together with a linear packet drop function for a heavy traffic load condition respectively. Results from ns-3 network simulator using different experimental scenarios clearly reveals that the proposed RED-QL algorithm yields a substantial reduction in delay performance and indeed a reduced average queue size than other three representative AQM algorithms. RED-QL is robust, easy to implement and deploy in routers (both in software and hardware) as no more than the packet drop probability profile of the classic RED’s algorithm implementation needs modest alteration. |
Databáze: | OpenAIRE |
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