FLRED: an efficient fuzzy logic based network congestion control method

Abualhaj, Mosleh M.; Abu-Shareha, Ahmad Adel; Al-Tahrawi, Mayy M.

doi:10.1007/s00521-016-2730-9

Cited by 26 publications

(32 citation statements)

References 15 publications

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“…To ease the parameter sensitivity, various AQM methods used fuzzy logic with queue management. Examples of fuzzy-based AQM are FuzzyRED [13], DeepBlue [24], Fuzzy logic for GRED (GREDFL) [2], and FLRED [3]. To reduce the delay, various AQM methods were proposed, these are Gentle RED (GRED) [25], Adaptive RED (ARED) [26], Dynamic RED (DRED) [27], PI [28], AVQ [29] and DQRED [30].…”

Section: Related Workmentioning

confidence: 99%

“…To adaptively estimate the parameter settings AQMRD [17], CRED [5], Adaptive Threshold RED [11], Adaptive-AQMRD [18], Adaptive Tuning of Drop-Tail (ADT) [21], Adaptive BLUE [22], SPC [7], NARED [23] and LTRED [12]. To ease the parameter sensitivity FuzzyRED [13], DeepBlue [24], Fuzzy logic for GRED (GREDFL) [2], and FLRED [3]. To reduce the delay GRED [25], ARED [26], DRED [27], PI [28], AVQ [29] and DQRED [30] GRED [25] add more scenarios to those implemented in RED and implements packet dropping as the length of the queue increases.…”

Section: Goalmentioning

confidence: 99%

“…Because congestion has terrible consequences on the network performance, various AQM methods were proposed in the literature, each of which has a specific target in defeating one of these consequences. Random Early Detection (RED) is the first AQM method, which was proposed to overcome the limitation of the passive approach that was used to manage the buffer, which is called a tail drop [1][2][3]. Figure 1.…”

Section: Introductionmentioning

confidence: 99%

“…The ability to identify false congestion depends on the slow variation of aqlvalues over time by computing the average length while givinga high weight for the previous queue lengths and less weight for the current queue length. Accordingly, when temporary heavy traffic is passed by the router, the value of aql does not change significantly and thus prevent unnecessary dropping [3,6,7].…”

Section: Introductionmentioning

confidence: 99%

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Controlling Delay at the Router Buffer using Modified Random Early Detection

Abu-Shareha¹

2019

IJCNC

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Active Queue Management (AQM) methods are used to manage the buffer of the network routers and avoid the problems caused by network congestion, especially packet loss. Among various AQM methods that have been proposed in the literature, Random Early Detection (RED)method has proved to stabilize the network performance under various traffic loads. However, as the primary concern of RED is to avoid loss when the router buffer overflowed, RED harms the delay at the router and increases the latency. Given that reducing delay is critical to some applications, such as online conferencing and broadcasting, RED needs to be adjusted to ease the delay problem. In this paper, RED is improved by monitoring the delay at the router buffer and implementing packet dropping to handle the issue of network delay and enhance the network performance. Accordingly, the modified method calculates and used a delay parameter with the RED to reduce the delay while maintaining the desirable RED's characteristics. The experimental results showed that the proposed Delay-Controller Random Early Detection (DcRED) improved network performance under various traffic loads. Compared to RED, DcRED results in less delay, while maintaining the loss and dropping rates.

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Section: Related Workmentioning

confidence: 99%

Section: Goalmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Controlling Delay at the Router Buffer using Modified Random Early Detection

Abu-Shareha¹

2019

IJCNC

Self Cite

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“…Every packet arriving at the router buffer is considered overflow and dropped as well as causing congestion [6][7][8]. Of average delay (D) and mean queue length (mql) of packets in the router buffer which also decreases the amount of packets going in the router buffer (T) [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Stabilizing Average Queue Length in Active Queue Management Method

Baklizi¹

2019

ijacsa

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This paper proposes the Stabilized (DGRED) method for congestion detection at the router buffer. This method aims to stabilize the average queue length between allocated minthre_shold and doublemaxthre_shold positions to increase the network performance. The SDGRED method is simulated and compared with Gentle Random Early Detection (GRED) and Dynamic GRED active queue management methods. This comparison is built on different important measures, such as dropping probability, throughput, average delay, packet loss, and mean queue length for packets. The evaluation aims to identify which method presents better simulation performance measurement results when noncongestion or congestion situations occur at the router buffers in congestion control. The results show that at high packet arrival probability, the proposed algorithm helps provide lesser queue length values, delayed time, and packet loss compared with current methods. Furthermore, SDGRED generates adequate throughput at high packet arrival probability.

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Fuzzy Logic Systems for Transmission Control Protocol

Molia

Kothari

2019

Lecture Notes in Electrical Engineering

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FLRED: an efficient fuzzy logic based network congestion control method

Cited by 26 publications

References 15 publications

Controlling Delay at the Router Buffer using Modified Random Early Detection

Controlling Delay at the Router Buffer using Modified Random Early Detection

Stabilizing Average Queue Length in Active Queue Management Method

Fuzzy Logic Systems for Transmission Control Protocol

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