Rate-Based Active Queue Management for Congestion Control Over Wired and Wireless Links

Wang, Jun; Song, Min; Yang, Houjun

doi:10.1109/chinacom.2006.344692

Cited by 9 publications

(6 citation statements)

References 11 publications

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“…Hybrid-based methods were proposed in the literature to solve the problems of the queue-based and load-based methods. Hybrid-based methods, such as REM [32] and REAQM [33], used independent congestion indicators that speculate the queue status and the traffic load. Different strategies were used for combining these congestion indications.…”

Section: Previous Workmentioning

confidence: 99%

Integrated Random Early Detection for Congestion Control at the Router Buffer

Abu-Shareha¹

2022

Computer Systems Science and Engineering

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This paper proposed an Integrated Random Early Detection (IRED) method that aims to resolve the problems of the queue-based AQM and loadbased AQM and gain the benefits of both using indicators from both types. The arrival factor (e.g., arrival rate, queue and capacity) and the departure factors are used to estimate the congestion through two integrated indicators. The utilized indicators are mathematically calculated and integrated to gain unified and coherent congestion indicators. Besides, IRED is built based on a new dropping calculation approach that fits the utilized congestion indicators while maintaining the intended buffer management criteria, avoiding global synchronization and enhancing the performance. The results showed that IRED, compared to RED, BLUE, ERED, FLRED, EnRED and DcRED, decreased packet delay and loss under various network status. Specifically, the results showed that in heavy and moderate traffic, the proposed IRED method outperformed the state-of-the-art methods in loss and delay by 18% and 10.6%, respectively.

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Section: Previous Workmentioning

confidence: 99%

Integrated Random Early Detection for Congestion Control at the Router Buffer

Abu-Shareha¹

2022

Computer Systems Science and Engineering

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“…The traffic-rate-based algorithms have been proposed in [5][6][7]. [6] proposes RAQM algorithm which uses aggregated traffic rate to calculate PDP.…”

Section: Related Workmentioning

confidence: 99%

“…[7] estimate traffic rate using EWMA, but it is not applicable to estimation of self-similar and high dynamic traffic. [5] proposes a rate-based AQM algorithm REAQM. It uses the mismatch between the incoming traffic rate and the link capacity as the primary metric and uses queue length as the second metric to calculate the mismatch coefficient.…”

Section: Related Workmentioning

confidence: 99%

“…Upon receiving this information, the host decreases its sending rate, so congestion can be avoided or mitigated. Current AQM algorithms can be mainly cataloged into following types: queue-size-based [3,4], traffic-rate-based [5][6][7], the combination of queue-size-based and rate-based [8], control-theory-based [9][10][11][12], etc. In fact, each AQM algorithm includes two parts: one part estimates the incipient congestion and the other part makes dropping decision based on the estimation.…”

Section: Introductionmentioning

confidence: 99%

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A novel adaptive traffic prediction AQM algorithm

Guo

Gao

et al. 2010

Telecommun Syst

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In the Internet, network congestion is becoming an intractable problem. Congestion results in longer delay, drastic jitter and excessive packet losses. As a result, quality of service (QoS) of networks deteriorates, and then the quality of experience (QoE) perceived by end users will not be satisfied. As a powerful supplement of transport layer (i.e. TCP) congestion control, active queue management (AQM) compensates the deficiency of TCP in congestion control. In this paper, a novel adaptive traffic prediction AQM (AT-PAQM) algorithm is proposed. ATPAQM operates in two granularities. In coarse granularity, on one hand, it adopts an improved Kalman filtering model to predict traffic; on the other hand, it calculates average packet loss ratio (PLR) every prediction interval. In fine granularity, upon receiving a packet, it regulates packet dropping probability according Z. Na ( ) School to the calculated average PLR. Simulation results show that ATPAQM algorithm outperforms other algorithms in queue stability, packet loss ratio and link utilization.

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“…However, these methods used joint monitoring indicators rather than using AQL or IQL independently. [22], rate-based AQM (REAQM) [39], SVB [13], stable rate-based AQM (RAQM) [38] and robust active queue management (RaQ) [35].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Comprehensive Random Early Detection of Router Congestion

Abu-Shareha

Al-Kasasbeh²,

Shambour³

et al. 2022

ITC

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The queue length and the load rate should be monitored to overcome the problem of router congestion due to the increase in network utilization and achieve a high-speed transmission. Previous active queue management methods manage the queued packets in the router buffer to maintain high network performance. However, these methods depend on monitoring indicators that do not cover all the congestion signs, leading to packet loss and delay. Accordingly, all the congestion signs should be wrapped into these indicators and managed by an algorithm that randomly drops packets to avoid global synchronization, loss, and delay. In this paper, a fuzzy comprehensive random early detection (FCRED) is proposed to deal with the gap in network monitoring and congestion control at the router buffer. FCRED is built by using three indicators, which monitor the router's arrival, departure, and queue length. Accordingly, a fuzzy inference process is developed to manage these indicators and calculate the dropping probability (Dp). Simulation results show that FCRED improves loss and packet dropping under various network statuses compared with RED, BLUE, and ERED. In terms of loss, FCRED achieves zero loss at high congested status. For dropping, FCRED achieves an optimal rate of 0.47 with an arrival rate of 0.95. For the throughput and delay, FCRED achieves the best results. Accordingly, the proposed FCRED method achieves zero loss and reduces packet dropping from 0.28 to 0.21, a 25% reduction compared with the best performance of these methods. Compared with recent fuzzy-based methods, the proposed FCRED achieves comparable results and outperforms them by dropping more packets to avoid loss, which in such case is necessary dropping.

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Rate-Based Active Queue Management for Congestion Control Over Wired and Wireless Links

Cited by 9 publications

References 11 publications

Integrated Random Early Detection for Congestion Control at the Router Buffer

Integrated Random Early Detection for Congestion Control at the Router Buffer

A novel adaptive traffic prediction AQM algorithm

Fuzzy Comprehensive Random Early Detection of Router Congestion

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