Adaptive Queue Management Based On the Change Trend of Queue Size

Tang, Liangrui; Tan, Yaomu

doi:10.3837/tiis.2019.03.013

Cited by 3 publications

(2 citation statements)

References 29 publications

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“…However, the aggressive dropping method used in AQMRD results in low link utilization, lengthy delays, and a high loss rate. Change Trend Queue-Management (CT-AQM) is a novel AQM algorithm that Tang and Tan designed so as to increase the reaction time of RED scheme (Tang, L. & Tan, Y., 2019). In order to determine packet drop probabilities, CT-AQM forecasts the change trend of queue size based on the change rate of the traffic load and average queue length (avg).…”

Section: Related Workmentioning

confidence: 99%

“…The poor performance of the RED algorithm can be related with its linear drop function, that tends to be extremely aggressive when traffic load is low and not aggressive enough at high loads (Bonald, T., et al, 2015 andKorolkova, A., et al, 2019). To address the weakness of RED, several improved variants of RED were developed, such as Gentle RED (Floyd S., 2000), Adaptive RED (Floyd, S., et al, 2001), Double Slope RED (Zheng, B., 2006), Nonlinear RED (Zhou, K., et al, 2006) Autonomous RED (Ho, H. J., & Lin, W. M., 2008), Cautious Adaptive (Tahiliani, M. P., et al, 2011), Improved Nonlinear RED (Zhang et al, 2012, Three Section RED (Feng, C., et al, 2014), Adaptive queue management with random dropping (Karmeshu et al, 2017), Change Trend Queue Management (Tang, L. & Tan, Y., 2019), Quadratic RED (Kumhar, D., et al, 2021), Quadratic Exponential RED (Hassan, S., et al, 2023), etc. Despite all of these improvements, whenever there is changes in the traffic load, the impact of congestion control will be significantly impacted.…”

Section: Introductionmentioning

confidence: 99%

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Exponential-Self-Adaptive Random Early Detection Scheme for Queue Management in Next Generation Routers

Surajo,

Suleiman,

Yahaya

2023

FJS

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ensuring optimal performance in next-generation routers. Active Queue Management (AQM) scheme, has been advocated by the Internet research community for the next generation routers. Random Early Detection (RED) is the most well-known AQM scheme. However, RED lacks self-adaptation mechanism and it is susceptible to parametrization problem. Several variants of RED were developed, however all of them possess a static drop pattern; as such they are severely affected when a traffic load changes. To address the self-adaptation shortcoming of the RED and its variant schemes, Self-Adaptive Random Early Detection (SARED) scheme was developed. However, to avoid congestion, SARED aggressively drops packets once the queue length reached a certain maximum threshold limit, subsequently, this will increase the average queuing delay for networks with high traffic load conditions, therefore, to eliminate the aggressiveness of SARED in such situations, an Exponential version of SARED was proposed in this paper. Results of the simulation experiments carried out have indicated that in high traffic load situations, Exponential-SARED (ESARED) has significantly reduced average queuing delay by 4% and maximized average throughput by 3% compared to SARED and QERED.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exponential-Self-Adaptive Random Early Detection Scheme for Queue Management in Next Generation Routers

Surajo,

Suleiman,

Yahaya

2023

FJS

View full text Add to dashboard Cite

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A Novel Active Queue Management Algorithm Based on Average Queue Length Change Rate

et al. 2022

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The rapid development of information technology has promoted the transformation of traditional networks into intelligent networks. Huge data traffic is generated by various types of traffic services in the intelligent networks, which can easily lead to network congestion, system instability, and other problems. These problems may incur great requirements and pose challenges for queue management algorithms. Most traditional active queue management (AQM) algorithms judge the congestion level of the network based only on the size of the average queue length while ignoring the network traffic variations. This makes these algorithms difficult to achieve effective improvement of congestion control efficiency. To address this problem, a novel network congestion control algorithm, namely the average queue length and change rate -RED (AC-RED) is proposed in this paper. AC-RED can better relieve network congestion by reconfiguring the packet loss strategy model based on the average queue length change rate. The simulation results of NS2 show that in complex and dynamic network environments, the performance of AC-RED algorithm in the average queue length, packet loss rate, delay, and delay jitter is improved in most load conditions compared with the other five algorithms.INDEX TERMS Active queue management; network congestion; average queue length change rate; AC-RED; NS2

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An Active Queue Management Algorithm to Guarantee the QoS of LEO Satellite Network

Hou

Yang

Liu

et al. 2023

2023 3rd International Symposium on Computer Technology and Information Science (ISCTIS)

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Adaptive Queue Management Based On the Change Trend of Queue Size

Cited by 3 publications

References 29 publications

Exponential-Self-Adaptive Random Early Detection Scheme for Queue Management in Next Generation Routers

Exponential-Self-Adaptive Random Early Detection Scheme for Queue Management in Next Generation Routers

A Novel Active Queue Management Algorithm Based on Average Queue Length Change Rate

An Active Queue Management Algorithm to Guarantee the QoS of LEO Satellite Network

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