On the analysis of RED algorithm in ZigBee network for queue management

Biddut, Md. Jaminul Haque; Islam, Nazrul; Arif, Md. Faizul Huq; Rahman, Md. Syfur

doi:10.1109/iciev.2016.7760036

Cited by 5 publications

(1 citation statement)

References 13 publications

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“…RED has a higher throughput fairness than Tail-Drop [23,24]. Some studies have reported on the usefulness of RED for the congestion control of wireless networks [25][26][27]. RED controls congestion more rapidly than typical end-to-end algorithms but is also compatible with them [28].…”

Section: Introductionmentioning

confidence: 99%

Effects on random early detection of the packet drop probability function with an adjustable nonlinearity

Kato

Asahara

et al. 2023

NOLTA

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This paper proposed a packet drop probability function with an adjustable nonlinearity parameter in random early detection (RED) for active queue management of a router to control network congestion. We investigated the effect of nonlinearity on the average queue size, average throughput, average retransmission rate, average round-trip time, and fairness index for two widely used loss-based congestion control algorithms: Reno and CUBIC. Simulations were performed with Tail-Drop and the original RED to clarify the effect of nonlinearity under different traffic loads. The results showed that the RED with a nonlinear function did not aggravate the network performance statistics because achieved high throughput while maintaining a low-queuing delay, such as the original RED with a linear function under the extremely heavy traffic condition. Under the light and the heavy traffic conditions, increasing the bending degree of the nonlinear function accomplished high throughput by preventing excessive discarding of packets.

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