Linear Random Early Detection for Congestion Control at the Router Buffer

Abu-Shareha, Ahmad Adel; Al-Kasasbeh, Basil; Shambour, Qusai; Abualhaj, Mosleh M.; Alsharaiah, Mohmmad Abdalla; Al-Khatib, Sumaya N.

doi:10.31449/inf.v46i5.3966

Cited by 3 publications

(3 citation statements)

References 25 publications

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“…In such a case, the congestion responsiveness was improved, and the performance was stabilized as the value of Dp was stabilized. Linear RED (LRED) [34] developed a linear equation with calculations to reduce the complexity of RED. Integrated RED (IRED) [35] used arrival, departure, and queue length factors to improve the AQM performance.…”

Section: The Crisp-based Aqm Methodsmentioning

confidence: 99%

Fuzzy-Based Active Queue Management Using Precise Fuzzy Modeling and Genetic Algorithm

Abu-Shareha,

Alsaaidah,

Alshahrani

et al. 2023

Symmetry

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Active Queue Management (AQM) methods significantly impact the network performance, as they manage the router queue and facilitate the traffic flow through the network. This paper presents a novel fuzzy-based AQM method developed with a computationally efficient precise fuzzy modeling optimized using the Genetic Algorithm. The proposed method focuses on the concept of symmetry as a means to achieve a more balanced and equitable distribution of the resources and avoid bandwidth wasting resulting from unnecessary packet dropping. The proposed method calculates the dropping probability of each packet using a precise fuzzy model that was created and tuned in advance and based on the previous dropping probability value and the queue length. The tuning process is implemented as an optimization problem formulated for the b0, b1, and b2 variables of the precise rules with an objective function that maximizes the performance results in terms of loss, dropping, and delay. To prove the efficiency of the developed method, the simulation was not limited to the common Bernoulli process simulation; instead, the Markov-modulated Bernoulli process was used to mimic the burstiness nature of the traffic. The simulation is conducted on a machine operated with 64-bit Windows 10 with an Intel Core i7 2.0 GHz processor and 16 GB of RAM. The simulation used Java programming language in Apache NetBeans Integrated Development Environment (IDE) 11.2. The results showed that the proposed method outperformed the existing methods in terms of computational complexity, packet loss, dropping, and delay. As such, in low congested networks, the proposed method maintained no packet loss and dropped 22% of the packets with an average delay of 7.57, compared to the best method, LRED, which dropped 21% of the packets with a delay of 10.74, and FCRED, which dropped 21% of the packets with a delay of 16.54. In highly congested networks, the proposed method also maintained no packet loss and dropped 48% of the packets, with an average delay of 16.23, compared to the best method LRED, which dropped 47% of the packets with a delay of 28.04, and FCRED, which dropped 46% of the packets with a delay of 40.23.

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Section: The Crisp-based Aqm Methodsmentioning

confidence: 99%

Fuzzy-Based Active Queue Management Using Precise Fuzzy Modeling and Genetic Algorithm

Abu-Shareha,

Alsaaidah,

Alshahrani

et al. 2023

Symmetry

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show abstract

“…In [10], linear RED or (LRED) utilizes an adaptive average queue size, which is a simplified congestion measure and a linear drop function that has a reduced number of operators. This way, RED's computational cost was reduced.…”

Section: Related Workmentioning

confidence: 99%

“…In the Internet, congestion control is considered a germane and in fact a research hotspot for scholars in the field of data communications and computer networks ( [7], [9]). To ensure a good network performance, there is a need to effectively and properly manage the queue in the buffer of network routers [10].…”

Section: Introductionmentioning

confidence: 99%

Double Function Random Early Detection (DFRED): A Revised RED-Oriented Algorithm

Hassan,

Ajaegbu,

Solanke

2023

Iraqi Journal of Science

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Dropping packets with a linear function between two configured queue thresholds in Random Early Detection (RED) model is incapable of yielding satisfactory network performance. In this article, a new enhanced and effective active queue management algorithm, termed Double Function RED (DFRED in short) is developed to further curtail network delay. Specifically, DFRED algorithm amends the packet dropping probability approach of RED by dividing it into two sub-segments. The first and second partitions utilizes and implements a quadratic and linear increase respectively in the packet dropping probability computation to distinguish between two traffic loads: low and high. The ns-3 simulation performance evaluations clearly indicate that DFRED algorithm significantly controls the average queue occupancy and yields a reasonable gain in end-to-end-delay under different network conditions.

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Modified dropping-random early detection (MD-RED): a modified algorithm for controlling network congestion

Hassan

Rufai

2023

Int. j. inf. tecnol.

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Linear Random Early Detection for Congestion Control at the Router Buffer

Cited by 3 publications

References 25 publications

Fuzzy-Based Active Queue Management Using Precise Fuzzy Modeling and Genetic Algorithm

Fuzzy-Based Active Queue Management Using Precise Fuzzy Modeling and Genetic Algorithm

Double Function Random Early Detection (DFRED): A Revised RED-Oriented Algorithm

Modified dropping-random early detection (MD-RED): a modified algorithm for controlling network congestion

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