Essay On The Study Of The Self-Oscillating Regime In The Control System

Korolkova, Anna V.; Kulyabov, Dmitry S.; Velieva, Tatyana R.; Zaryadov, I. S.

doi:10.7148/2019-0473

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…11 and 12, it can be observed that, for RED and TRED in their respective high-load scenarios, the queue length hit the maximum threshold value (max th ) several times. This indicated several forced drops and, subsequently, global synchronization [3,16,24]. The results presented in Fig.…”

Section: Simulation Experimentsmentioning

confidence: 91%

“…Even though the RED algorithm provides better performance than the tail-drop approach, several works have revealed that RED suffers from some shortcomings, such as sensitivity to parameter settings and the lack of a self-adaptation mechanism [3,8,16,17,19,20,24].…”

Section: Related Workmentioning

confidence: 99%

“…Although RED outperforms the tail-drop approach, it was discovered that the effect of RED's congestion management is seriously affected once a traffic load changes, since RED is highly sensitive to its parameter settings and network's traffic condition changes frequently; thus, constant tuning of RED's parameters is required to achieve the desired performance [3,8,16,17,19,20,24]. Additionally, RED's poor performance can also be associated with its linear drop function, which tends to be too aggressive at low loads and not aggressive enough when avg approaches max th [20,27].…”

Section: Introductionmentioning

confidence: 99%

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SARED: A Self-Adaptive Active Queue Management Scheme for Improving Quality of Service in Network Systems

Adamu¹

2021

csci

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Considering the phenomenal growth of network systems, congestion remains a threat to the quality of service provided in such systems, hence, research on congestion control is still relevant. Internet research community regards Active Queue Management (AQM) as an effective approach to address congestion in network systems. Most of the existing AQM schemes possess static drop patterns and lack self-adaptation mechanism, as such don’t work well for networks where traffic load fluctuates. This paper proposes Self-Adaptive Random Early Detection (SARED) scheme which smartly adapts its drop pattern based on current network’s traffic load in order to maintain better and stable performance. In light to moderate load conditions, SARED operates in nonlinear modes in order to maximize utilization and throughput, while in high load condition, it switches to linear mode in order to avoid forced drops and congestion. Experiments conducted have revealed that regardless of traffic load’s condition, SARED provides optimal performance.

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Section: Simulation Experimentsmentioning

confidence: 91%