QLREDActive Queue Management Algorithm

2021 ◽  
Vol 28 (1) ◽  
Author(s):  
S.O. Hassan ◽  
A.O. Oluwatope ◽  
C. Ajaegbu ◽  
K-K.A. Abdullah ◽  
A.O. Olasupo
Keyword(s):  
Queue Size ◽  
Packet Dropping ◽  
Simulation Performance ◽  
Internet Routers ◽  
Dropping Probability ◽  
Management Algorithm ◽  
Traffic Loads ◽  
Probability Profile ◽  
Dropping Function ◽  
Minimal Effort

The Random Early Detection (RED) algorithm has not been successful in keeping the average queue size low. In this paper, we an improved RED-based algorithm called QLRED which divides the dropping probability function of the RED algorithm into two equal segments. The first segment utilises a quadratic packet dropping function while the second segment deploys a linear packet dropping function respectively so as to distinguish between light and high traffic loads. The ns-3 simulation performance evaluations clearly showed that QLRED algorithm effectively controls the average queue size under various network conditions resulting in a low delay. Replacing/upgrading the RED algorithm in Internet routers requires minimal effort since only the packet dropping probability profile needs to be adjusted.

scholarly journals On the Transient Queue with the Dropping Function

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 825
Author(s):  
Andrzej Chydzinski
Keyword(s):  
Queueing System ◽  
Transient Behavior ◽  
Time Interval ◽  
Queue Size ◽  
Internet Routers ◽  
Management Schemes ◽  
Natural Characteristic ◽  
Dropping Function ◽  
Theoretical Results ◽  
Steady State Performance

We deal with a queueing system, in which arriving packets are being dropped with the probability depending on the queue size. Such a scheme is used in several active queue management schemes proposed for Internet routers. In this paper, we derive and analyze a selected transient characteristic of the model, i.e., the probability that in a given time interval the queue size is kept under a predefined level. As the main purpose of the discussed queueing scheme is to maintain the queue size low, this is a natural characteristic to study. In addition to that, the average time to reach a given level is derived. Theoretical results for both characteristics are accompanied by numerical examples. Among other things, they demonstrate that the transient behavior of the queue may vary significantly with the shape of the dropping function, even if the steady-state performance remains unaltered.

scholarly journals Analysis of AQM queues with queue size based packet dropping

2011 ◽  
Vol 21 (3) ◽  
pp. 567-577 ◽  
Author(s):  
Andrzej Chydziñski ◽  
Łukasz Chróst
Keyword(s):  
Size Distribution ◽  
Analytical Solutions ◽  
Queueing Systems ◽  
Queue Management ◽  
Queue Size ◽  
Loss Ratio ◽  
Packet Dropping ◽  
Numerical Examples ◽  
Internet Routers ◽  
Blocking Probabilities

Analysis of AQM queues with queue size based packet dropping Queueing systems in which an arriving job is blocked and lost with a probability that depends on the queue size are studied. The study is motivated by the popularity of Active Queue Management (AQM) algorithms proposed for packet queueing in Internet routers. AQM algorithms often exploit the idea of queue-size based packet dropping. The main results include analytical solutions for queue size distribution, loss ratio and throughput. The analytical results are illustrated via numerical examples that include some commonly used blocking probabilities (dropping functions).

ADAPTIVE SCHEMES FOR REDUCING POWER CONSUMPTION OF MOBILE DATA HANDSETS

2001 ◽  
Vol 02 (01) ◽  
pp. 69-84
Author(s):  
RONG-JAYE CHEN ◽  
TING-YU LIN ◽  
YI-BING LIN
Keyword(s):  
Power Consumption ◽  
Adaptive Algorithm ◽  
Threshold Value ◽  
Fixed Amount ◽  
Mobile Data ◽  
Packet Dropping ◽  
Dropping Probability ◽  
Adaptive Schemes ◽  
Binary Division ◽  
Threshold Approach

This paper describes a threshold-based wake-up mechanism to reduce the battery power consumption of a mobile data handset. The threshold approach switches the system into the sleep mode when the memory queue for arriving packets is empty, and switches on the system when the number of packets in the memory queue is above a threshold value. We propose several adaptive schemes capable of dynamically selecting the threshold value for the threshold approach. An adaptive algorithm adjusts the threshold value based on a pre-defined packet-dropping probability, for which the switch-on rate is kept reasonably small to maintain the actual packet-dropping probability as close as the pre-defined value. Two strategies are used in the adaptive algorithm to adjust the threshold value: binary-division and fixed-amount. Two calculation strategies are considered to measure the packet-dropping probability: window-averaging and leaky-bucket integration (LBI). Our study indicates that the binary-division strategy outperforms the fixed-amount strategy in adjusting the threshold value. Furthermore, with proper setting, the LBI strategy outperforms the window-averaging strategy.

HRED, An Active Queue Management Algorithm for TCP Congestion Control

2019 ◽  
Vol 12 (3) ◽  
pp. 212-217
Author(s):  
Nabhan Hamadneh ◽  
Mamoon Obiedat ◽  
Ahmad Qawasmeh ◽  
Mohammad Bsoul
Keyword(s):  
Management Strategies ◽  
Active Queue Management ◽  
Queue Management ◽  
Queue Size ◽  
Management Algorithm ◽  
Link Utilization ◽  
Parameter Configuration ◽  
History Of ◽  
Packet Drop ◽  
Drop Rate

Background: Active Queue Management (AQM) is a TCP congestion avoidance approach that predicts congestion before sources overwhelm the buffers of routers. Random Early Detection (RED) is an AQM strategy that keeps history of queue dynamics by estimating an average queue size parameter avg and drops packets when this average exceeds preset thresholds. The parameter configuration in RED is problematic and the performance of the whole network could be reduced due to wrong setup of these parameters. Drop probability is another parameter calculated by RED to tune the drop rate with the aggressiveness of arriving packets. Objective: In this article, we propose an enhancement to the drop probability calculation to increase the performance of RED. Methods: This article studies the drop rate when the average queue size is at the midpoint between the minimum and maximum thresholds. The proposal suggests a nonlinear adjustment for the drop rate in this area. Hence, we call this strategy as the Half-Way RED (HRED). Results: Our strategy is tested using the NS2 simulator and compared with some queue management strategies including RED, TD and Gentle-RED. The calculated parameters are: throughput, link utilization and packet drop rate. Conclusion: Each performance parameter has been plotted in a separate figure; then the robustness of each strategy has been evaluated against these parameters. The results suggest that this function has enhanced the performance of RED-like strategies in controlling congestion. HRED has outperformed the strategies included in this article in terms of throughput, link utilization and packet loss rate.

An Intelligent Fuzzy Logic System for Network Congestion Control

2017 ◽  
Vol 2 (11) ◽  
pp. 23-30 ◽  
Author(s):  
Uguta Henry Preye ◽  
Onyejegbu Laeticia Nneka
Keyword(s):  
Fuzzy Logic ◽  
Queue Length ◽  
Network Performance ◽  
Early Stage ◽  
Fuzzy Logic System ◽  
Queue Size ◽  
Network Congestion ◽  
Inference System ◽  
Dropping Probability ◽  
Logic System

Network congestion is a major problem in all network environments as such it calls for ways to manage this problem. In this paper, we propose a Fuzzy Regulator Effective Random Early Detection (FRERED) system, which is an intelligent fuzzy logic based controller technique for early stage congestion detection, at the router buffer in the networks. The proposed technique extends the Fuzzy-Based system in the Fuzzy Hybrid ERED algorithm by considering the delay variable in its inference system to ease the problem of parameter initialization and parameter dependency. Unlike the Fuzzy-Based controller in the existing Fuzzy Hybrid ERED system which uses two parameter settings in its inference system that is, the queue size and average queue length in computing the dropping probability of packets. The proposed technique uses the queue size, average queue length and the delay approximation as input variables in computing the packet drop probability. The applied fuzzy logic system yields an output that denotes a packet dropping probability, which in turn controls and prevents congestion in early stage. This was achieved after simulating the proposed technique and the existing Fuzzy-Based controller using Matlab. The results obtained shows that this approach results in less packet drops for about the same link utilization as the existing Fuzzy-Based controller. Therefore, this technique, generally, controls network congestion and improves network performance. The methodology used to achieve this is the object oriented methodology and JAVA programming language was used to develop the system.

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