Fuzzy Logic Control in Communication Networks

Chrysostomou, Chrysostomos; Pitsillides, Andreas

doi:10.1007/978-3-642-01533-5_8

Cited by 5 publications

(3 citation statements)

References 49 publications

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“…Several techniques are presented to overcome network congestion. One such method is fuzzy logic which is actively utilized in wireless sensor networks for different applications [13]. Fuzzy logic is close to natural language comparing with the traditional logical systems which can capture the approximate real-world nature.…”

Section: Fuzzy Logic-based Congestion Control Schemes In Wsnsmentioning

confidence: 99%

“…Fuzzy logic is close to natural language comparing with the traditional logical systems which can capture the approximate real-world nature. The Fuzzy Inference System (FIS) includes the Fuzzification, the Rule Base, the Inference Mechanism and the Defuzzification interface module [13]. Fuzzy logic-based congestion control can be considered as one of the latest approaches to control congestion.…”

Section: Fuzzy Logic-based Congestion Control Schemes In Wsnsmentioning

confidence: 99%

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Soft Computing-Based Congestion Control Schemes in Wireless Sensor Networks: Research Issues and Challenges

Farahani

2021

mjee

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Wireless Sensor Networks (WSNs) are a special class of wireless ad-hoc networks where their performance is affected by different factors. Congestion is of paramount importance in WSNs. It badly affects channel quality, loss rate, link utilization, throughput, network life time, traffic flow, the number of retransmissions, energy, and delay. In this paper, congestion control schemes are classified as classic or soft computing-based schemes. The soft computing-based congestion control schemes are classified as fuzzy logic-based, game theory-based, swarm intelligence-based, learning automata-based, and neural network-based congestion control schemes. Thereafter, a comprehensive review of different soft computing-based congestion control schemes in wireless sensor networks is presented. Furthermore, these schemes are compared using different performance metrics. Finally, specific directives are used to design and develop novel soft computing-based congestion control schemes in wireless sensor networks.

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Section: Fuzzy Logic-based Congestion Control Schemes In Wsnsmentioning

confidence: 99%

Section: Fuzzy Logic-based Congestion Control Schemes In Wsnsmentioning

confidence: 99%

Soft Computing-Based Congestion Control Schemes in Wireless Sensor Networks: Research Issues and Challenges

Farahani

2021

mjee

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“…Ignaciuk and Bartoszewicz [12] proposed a flow controller based on sliding-mode concept for congestion control in connection-oriented communication networks which are modelled as discrete-time n th-order systems. Chrysostomou et al [13] again attempted fuzzy based congestion control in Communication Networks. Nannan et al [14] analyze and control congestion in diffserv networks using second order sliding mode controllers to solve infinite switching problems.…”

Section: Introductionmentioning

confidence: 99%

A Novel Neural Network based Model Predictive Controller for Congestion Prevention in IP Networks

Baweja¹

2020

IJATCSE

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Design of a neural network based model predictive controller for UDP(User Datagram Protocol) flow caused congestion, in IP( Internet protocol) networks is proposed in this paper. The objectives of congestion control are prevention of congestion collapse, maximum network bandwidth utilization, TCP-friendliness and smoothness for streaming media applications. Various approaches for controlling congestion in networks are present in the literature. Many of these are make use of network models, which are already identified. In this paper a neural network utilizing Levenberg-Marquardt learning algorithm for on-line identification of non-linear plant(network) model is implemented and combined with a model predictive optimization technique using back tracking line search routine over a specified time horizon. Simulations were carried out to prove the effectiveness of the designed controller. Significant increase in the network bandwidth utilization is also established.

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