2022
DOI: 10.1038/s41598-022-17528-x
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Improving RED algorithm congestion control by using the Markov decision process

Abstract: Congestion control plays an essential role on the internet to manage overload, which affects data transmission performance. The random early detection (RED) algorithm belongs to active queue management (AQM), which is used to manage internet traffic. The RED is used to eliminate weakness in default control of the Transport Control Protocol (TCP) drop-tail mechanism. The drawback of RED is parameter tuning, while adaptive RED (ARED) automatically adjusts these parameters. In this study, the suggested algorithm,… Show more

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Cited by 3 publications
(1 citation statement)
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“…The [21] implement the AQM algorithm with PID and fuzzy logic controller and also used social spider optimization to tune the AQM parameters in order to reduce the error of queue size. All these studies focus on adjusting parameters to find the optimal result in the TCP congestion avoidance phase, The researcher in [22] focuses on the slow startup phase of TCP flow rate by finding the optimal queue weight parameter of AQM using the Markov Decision Process method. also in this study, congestion control occurs during the TCP slow start phase to handle congestion caused by the rapidly changing exponential increase in the data load factor.…”
Section: Related Workmentioning
confidence: 99%
“…The [21] implement the AQM algorithm with PID and fuzzy logic controller and also used social spider optimization to tune the AQM parameters in order to reduce the error of queue size. All these studies focus on adjusting parameters to find the optimal result in the TCP congestion avoidance phase, The researcher in [22] focuses on the slow startup phase of TCP flow rate by finding the optimal queue weight parameter of AQM using the Markov Decision Process method. also in this study, congestion control occurs during the TCP slow start phase to handle congestion caused by the rapidly changing exponential increase in the data load factor.…”
Section: Related Workmentioning
confidence: 99%