scholarly journals A Fuzzy Logic Based Network Congestion Control Using Active Queue Management Techniques

2010 ◽  
Vol 2 (2) ◽  
pp. 273-284 ◽  
Author(s):  
I. K. Tabash ◽  
M. A. Mamun ◽  
A. Negi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Probability Function ◽  
Active Queue Management ◽  
Buffer Size ◽  
Queue Management ◽  
Passive Devices ◽  
Better Regulation ◽  
Ip Routers ◽  
Intelligent Approach

Conventional IP routers are passive devices that accept packets and perform the routing function on any input. Usually the tail-drop (TD) strategy is used where the input which exceeds the buffer capacity are simply dropped. In active queue management (AQM) methods routers manage their buffers by dropping packets selectively. We study one of the AQM methods called as random exponential marking (REM). We propose an intelligent approach to AQM based on fuzzy logic controller (FLC) to drop packets dynamically, keep the buffer size around desired level and also prevent buffer overflow. Our proposed approach is based on REM algorithm, which drops the packets by drop probability function. In our proposal we replace the drop probability function by a FLC to drop the packets, stabilize the buffer around the desired size and reduce delay. Simulation results show a better regulation of the buffer.  Keywords: Random exponential marking; Active queue management; Fuzzy logic controller; Pro-active queue management. © 2010 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved. DOI: 10.3329/jsr.v2i2.2786               J. Sci. Res. 2 (2), 273-284 (2010) 

scholarly journals Fuzzy-Logic Based Active Queue Management Using Performance Metrics Mapping into Multi-Congestion Indicators

2021 ◽  
Vol 21 (2) ◽  
pp. 29-44
Author(s):  
Mosleh M. Abualhaj ◽  
Mayy M. Al-Tahrawi ◽  
Abdelrahman H. Hussein ◽  
Sumaya N. Al-Khatib
Keyword(s):  
Fuzzy Logic ◽  
Network Performance ◽  
Performance Metrics ◽  
Early Stage ◽  
Active Queue Management ◽  
Traffic Load ◽  
Performance Criteria ◽  
Queue Management ◽  
Method Show

Abstract The congestion problem at the router buffer leads to serious consequences on network performance. Active Queue Management (AQM) has been developed to react to any possible congestion at the router buffer at an early stage. The limitation of the existing fuzzy-based AQM is the utilization of indicators that do not address all the performance criteria and quality of services required. In this paper, a new method for active queue management is proposed based on using the fuzzy logic and multiple performance indicators that are extracted from the network performance metrics. These indicators are queue length, delta queue and expected loss. The simulation of the proposed method show that in high traffic load, the proposed method preserves packet loss, drop packet only when it is necessary and produce a satisfactory delay that outperformed the state-of-the-art AQM methods.

scholarly journals Fluid flow approximation of time-limited TCP/UDP/XCP streams

2014 ◽  
Vol 62 (2) ◽  
pp. 217-225 ◽  
Author(s):  
J. Domańska ◽  
A. Domański ◽  
T. Czachórski ◽  
J. Klamka
Keyword(s):  
Fluid Flow ◽  
Traffic Congestion ◽  
Time Moment ◽  
Active Queue Management ◽  
Queue Management ◽  
Flow Approximation ◽  
Ip Routers ◽  
Control Traffic ◽  
Management Algorithms

Abstract This article presents the use of fluid flow approximation to model interactions between a set of TCP, UDP and XCP flows in the environment of IP routers using AQM (Active Queue Management) algorithms to control traffic congestion. In contrast to other works, independent UDP and TCP streams are considered and the model allows to start and end data transmissions in TCP, UDP and XCP streams at any time moment. It incorporates several Active Queue Management mechanisms: RED, NLRED, CHOKe.

scholarly journals Grey wolf optimizer based fuzzy-PI active queue management design for network congestion avoidance

2020 ◽  
Vol 18 (1) ◽  
pp. 199 ◽  
Author(s):  
Sana Sabah Sabry ◽  
Nada Mahdi Kaittan
Keyword(s):  
Fuzzy Logic ◽  
Communication Networks ◽  
Control Strategy ◽  
Queue Length ◽  
Active Queue Management ◽  
Linguistic Knowledge ◽  
Grey Wolf Optimizer ◽  
Queue Management ◽  
Grey Wolf ◽  
Research Attention

<p>Congestion is one of the most important issues in communication networks which has attracted much research attention. To ensure a stable TCP network, we can use active queue management (AQM for early congestion detection and router queue length regulation. In this study, it was proposed to use the Grey Wolf Optimizer (GWO) algorithm in designing a fuzzy proportional integral (fuzzy-PI) controller as a novel AQM for internet routers congestion control and for achieving a low steady-state error and fast response. The suggested Fuzzy logic-based network traffic control strategy permit us to deploy linguistic knowledge for depicting the dynamics of probability marking functions and ensures a more accurate use of multiple inputs to depict the   the network’s state. The possibility of incorporating human knowledge into such a control strategy using Fuzzy logic control methodology was demonstrated. The postulated controller was compared to proportion integral (PI) through several MATLAB simulation scenarios. The results indicated the stability of the postulated controller and its ability to attain a faster response in a dynamic network with varying network load and target queue length.</p>

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