Multi-objective Particle Swarm Optimization for Fuzzy Logic Based Active Queue Management

Nyirenda, Clement N.; Dawoud, D.S.

doi:10.1109/fuzzy.2006.1682010

Cited by 15 publications

(8 citation statements)

References 12 publications

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“…Distinguishing bursty traffic from probable congestion is another goal which AI promises to help AQM towards. A congestion detector using fuzzy logic has been devised [53] that not only inherits good behavior of classic AQM schemes but also the membership functions are automatically defined using PSO algorithm. Another example is a method [54] that uses neuro-fuzzy prediction to capture traffic bursts and correctly predicts incoming steady congestion.…”

Section: Developments To Aqmmentioning

confidence: 99%

FQL‐RED: an adaptive scalable schema for active queue management

et al. 2010

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SUMMARYIn a potentially congested network, random early detection (RED) active queue management (AQM) proved effective in improving throughput and average queuing delay. The main disadvantage of RED is its sensitive parameters that are impossible to estimate perfectly and adjust manually because of the dynamic nature of the network. For this reason, RED performs differently during different phases of a scenario and there is no guarantee that it will have optimal performance. Giving adaptability to RED has been the subject of broad research studies ever since RED was proposed. After a substantial study of AQM schemes and presenting a novel categorization for so-called modern approaches utilizing artificial intelligence tools to improve AQM, this paper proposes an algorithm enhancing RED as an add-on patch that makes minimal changes to the original RED. Being built on the basis of AQM schemes like ARED and Fuzzy-RED, this algorithm inherits adaptability and is able to adjust RED inaccurate parameters regarding network traffic status, trying to optimize throughput and average queuing delay in a scenario. This algorithm is a Q-learning method enhanced with a fuzzy inference system to provide RED with self-adaptation and improved performance as a result. Given the name of FQL-RED, this algorithm outperformed RED, ARED, and Fuzzy-RED, as the OPNET simulations show.

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Section: Developments To Aqmmentioning

confidence: 99%

FQL‐RED: an adaptive scalable schema for active queue management

et al. 2010

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“…Moreover effective information sharing plays a key role in functioning and evolution of modern society. Variety of methods and algorithms are proposed to minimize the effects of congestion in computer networks like sliding-mode algorithm [4], [6], fuzzy logic [7] and others [8], [9], [10]. Recently significant attention is paid to modelling and methods for piece-wise affine (PWA) systems [11], [13], [18], [19] nonlinear systems [12], [14] whereas stability issues are discussed e.g.…”

Section: Introductionmentioning

confidence: 99%

Congestion control in computer networks: Application of piece-wise affine controller and particle swarm optimization

Grzyb

Orłowski

2014

2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR)

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Congestion control plays a significant role in maintaining sufficient network throughput. Variety of methods and algorithms are proposed to solve the bottleneck issue. This paper describes a method based on a particle swarm optimization algorithm and piecewise affine controller for non-stationary, discrete, dynamical model of data exchange network. This solution allows active network nodes buffer utilization to be adapted to sudden unexpected network state changes. That leads to alleviate network congestion effects.

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“…The occurrence of congestions in communication networks is connected as well with limited interlinks bandwidth as finite hardware resources of network nodes involved in the packets transmission [5]. To alleviate the results of congestions appearance in data exchange networks, variety of methods and algorithms are proposed like sliding-mode algorithm [3,8], fuzzy logic [9] and others [10,11,12]. Remarkable attention is recently paid to modelling and methods for piece-wise affine (PWA) systems [13,15,19,21] nonlinear systems [14,16].…”

Section: Introductionmentioning

confidence: 99%

Feedback control system with PWA load dependent reference buffer occupancy for congestion control in computer networks

Grzyb

Orłowski

2016

ELECTROTECHNICAL REVIEW

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Congestion avoidance plays the significant role in increasing network reliability and efficiency. To minimize blockage effects, many methods and algorithms have been proposed. A method of active egress queue length control in use not to over on underutilize buffer occupancy in non-stationary, discrete, dynamical model of communication channel is described in this paper. This approach allows to optimize available network nodes resources to avoid congestions effects or to minimize or alleviate negative impact of these congestion on network throughput. Streszczenie. W artykule zaproponowano metodę aktywnego sterowania długości kolejki wyjściowej, w celu zminimalizowania niepożądanych efektów zatorów sieciowych. Metoda ta pozwala unikać sytuacji nadmiernego przepełnienia lub opróżnienia bufora wyjściowego. Do badań został wykorzystany niestacjonarny, dyskretny, dynamiczny model kanału komunikacyjnego. Takie podejście umożliwia optymalizację dostępnych zasobów w węzłach sieciowych.(Sterowanie zatorami w sieciach komputerowych z wykorzystaniem pętli sprzężenia zwrotnego oraz wartości referencyjnej odcinkowo afinicznie zależnej od zajętości bufora).

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Multi-objective Particle Swarm Optimization for Fuzzy Logic Based Active Queue Management

Cited by 15 publications

References 12 publications

FQL‐RED: an adaptive scalable schema for active queue management

FQL‐RED: an adaptive scalable schema for active queue management

Congestion control in computer networks: Application of piece-wise affine controller and particle swarm optimization

Feedback control system with PWA load dependent reference buffer occupancy for congestion control in computer networks

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