Flexible Random Early Detection Algorithm for Queue Management in Routers

Adamu, Abubakar; Shorgin, Vsevolod; Melnikov, Sergey Yu.; Gaidamaka, Yuliya

doi:10.1007/978-3-030-66471-8_16

Cited by 17 publications

(14 citation statements)

References 16 publications

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“…However, RED is sensitive to the parameter settings, a sudden increase in the packet drop probability may occur when the average queue length is greater than the queue length upper limit. FXRED, presented by Adamu et al [10], recognizes the state of the current network's traffic load and auto-tunes its drop probability suitable to the observed load situation to maintain stable and better performance. Su et al [11] use the Q-learning algorithm to achieve self-adaptive adjustment for the max p of RED.…”

Section: Related Workmentioning

confidence: 99%

SQM-LRU: A Harmony Dual-Queue Management Algorithm to Control Non-Responsive LTF Flow and Achieve Service Differentiation

Jiang

Zhu

et al. 2021

Sensors

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The increase in network applications diversity and different service quality requirements lead to service differentiation, making it more important than ever. In Wide Area Network (WAN), the non-responsive Long-Term Fast (LTF) flows are the main contributors to network congestion. Therefore, detecting and suppressing non-responsive LTF flows represent one of the key points for providing data transmission with controllable delay and service differentiation. However, the existing single-queue management algorithms are designed to serve only a small number of applications with similar requirements (low latency, high throughput, etc.). The lack of mechanisms to distinguish different traffic makes it difficult to implement differentiated services. This paper proposes an active queue management scheme, namely, SQM-LRU, which realizes service differentiation based on Shadow Queue (SQ) and improved Least-Recently-Used (LRU) strategy. The algorithm consists of three essential components: First, the flow detection module is based on the SQ and improved LRU. This module is used to detect non-responsive LTF flows. Second, different flows will be put into corresponding high or low priority sub-queues depending on the flow detection results. Third, the dual-queue adopts CoDel and RED, respectively, to manage packets. SQM-LRU intends to satisfy the stringent delay requirements of responsive flow while maximizing the throughput of non-responsive LTF flow. Our simulation results show that SQM-LRU outperforms traditional solutions with significant improvement in flow detection and reduces the delay, jitter, and Flow Completion Time (FCT) of responsive flow. As a result, it reduced the FCT by up to 50% and attained 95% of the link utilization. Additionally, the low overhead and the operations incur O(1) cost per packet, making it practical for the real network.

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Section: Related Workmentioning

confidence: 99%

SQM-LRU: A Harmony Dual-Queue Management Algorithm to Control Non-Responsive LTF Flow and Achieve Service Differentiation

Jiang

Zhu

et al. 2021

Sensors

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“…A serious problem of RED and its improved algorithms is that they ignore the changes in network traffic and judge the congestion of the network only concerning the average queue length. This means that the control efficiency of these algorithms cannot be improved effectively [22].…”

Section: Introductionmentioning

confidence: 99%

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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“…In the Internet, a key resource like routers play a crucial role of handling large traffic loads is affected by congestion [3]. Congestion has an adverse effect of degrading network performance [5]- [7]. Therefore, avoidance/control of congestion is imperative in order to ensure an improved quality of service for users on the Internet [7], [8].…”

Section: Introductionmentioning

confidence: 99%

“…Congestion has an adverse effect of degrading network performance [5]- [7]. Therefore, avoidance/control of congestion is imperative in order to ensure an improved quality of service for users on the Internet [7], [8]. Traditionally in Internet routers, DropTail algorithm drops packet only when the buffer is full.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improved random early detection congestion control algorithm for internet routers

Hassan

Rufai

Agbaje

et al. 2022

IJEECS

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In the internet, router plays a strategic role in the transmission of data packets. Active queue management (AQM) aimed at managing congestion by keeping a reduced average buffer occupancy and hence a minimal delay. The novel random early detection (RED) algorithm suffers from large average buffer occupancy and delay shortcomings. This problem is due in part to the existence of a distinctive linear packet drop function it deploys. In this paper, we present a new version of RED, called improved RED (IMRED). An important strategy of IM-RED is to deploy two dropping functions: i) nonlinear (i.e. quadratic) to deal with both light-and moderatenetwork traffic load conditions, and ii) linear to deal with heavy traffic load condition. Simulation experiments conducted using open-source ns-3 software to evaluate and compare the functionality of the proposed IM-RED with other two previous AQM algorithms confirmed that IM-RED reduces the average buffer occupancy and obtained an improved delay performance especially at heavy network traffic load scenario. Very fortunately, since RED algorithm is known to appear as a built-in model in ns-3 and even Linux kernel, its implementation can therefore be leveraged to obtain IMRED while only adjusting the packet dropping probability profile and holding on to its other attributes.

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Flexible Random Early Detection Algorithm for Queue Management in Routers

Cited by 17 publications

References 16 publications

SQM-LRU: A Harmony Dual-Queue Management Algorithm to Control Non-Responsive LTF Flow and Achieve Service Differentiation

SQM-LRU: A Harmony Dual-Queue Management Algorithm to Control Non-Responsive LTF Flow and Achieve Service Differentiation

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

Improved random early detection congestion control algorithm for internet routers

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