An Improved RED Algorithm with Input Sensitivity

Chhabra, Kiran; Kshirsagar, Manali; Zadgaonkar, A. S.

doi:10.1007/978-981-10-8536-9_5

Cited by 5 publications

(9 citation statements)

References 8 publications

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“…The adaptive mechanism calculates the values of the parameters as similar to the calculation of the indicator instead of using a fixed value. Accordingly, New Adaptive Random Early Detection (NARED) [33], Queue-Length Threshold Random Early Detection (LTRED) [9], and Priority Random Early Detection (PRED) [10] are adaptive congestion control methods. These methods, in general, did not focus on the results or improving the network performance.…”

Section: Previous Workmentioning

confidence: 99%

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Linear Random Early Detection for Congestion Control at the Router Buffer

Abu-Shareha¹,

Al-Kasasbeh²,

Shambour³

et al. 2022

IJCAI

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Active Queue Management (AQM) methods control the router's buffer to maintain high network performance and control congestion at the router buffer. Random Early Detection (RED) method is the most well-known and the most utilized AQM. RED suffers from a high dropping rate, which motivates the later AQM methods to use more complex processes, which reach the limits of using fuzzy systems as a processing technique. Yet, high computational cost affects the router's performance specifically and the network as a whole, with so-called processing delay. In this paper, a linear version of RED (LRED) is presented to reduce the computational cost of the original RED and maintain the network performance in terms of throughput, delay, dropping, and loss. LRED is built based on two distinctive features, simplifying the congestion indicator calculation and reducing the operations in calculating the dropping probability. The experimental results showed that the proposed method reduces the delay and the processing time while maintaining the throughput and loss of the RED method. Povzetek: Opisan je razvoj nove metode za upravljanje predpomnilnika na omrežju.

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Section: Previous Workmentioning

confidence: 99%

“…An optimized dropping should speculate the current queue and load statuses and the expected future status, which can be estimated based on the current and previous load status. These considerations are addressed in the congestion indicator(s) [9,10].…”

Section: Introductionmentioning

confidence: 99%

Linear Random Early Detection for Congestion Control at the Router Buffer

Abu-Shareha¹,

Al-Kasasbeh²,

Shambour³

et al. 2022

IJCAI

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“…For a fair resource allocation objective, which implemented by dropping packets based on the shared bandwidth consumed by each flow, Stabilized RED (SRED) [19] and Probability-based RED (P-RED) [20] methods were proposed. Various methods were proposed for adaptive parameterestimation, such as: AQMRD [17], CRED [5], Adaptive Threshold RED [11], Adaptive-AQMRD [18], Adaptive Tuning of Drop-Tail (ADT) [21], Adaptive BLUE [22], Self-Tuning Price-based Congestion Control (SPC) [7], New Adaptive RED (NARED) [23] and Queue-Threshold RED (LTRED) [12]. To ease the parameter sensitivity, various AQM methods used fuzzy logic with queue management.…”

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].…”

Section: Goalmentioning

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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