Fuzzy Logic Approach for Cluster-Head Election in Wireless Sensor Network

Abbas, Safana Hyder; Khanjar, Israa M.

doi:10.31695/ijerat.2019.3460

Cited by 6 publications

(4 citation statements)

References 11 publications

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“…The work in Shemim and Witkowski 16 studies various routing protocols effect on energy consumption using NS-2 simulator like Adaptive Clustering Hierarchy protocol (LEACH) 17 and Fuzzy-based routing protocols. 18 The WSN is simulated WSN sensors (i.e. modeled as NS-2 nodes) where the overall network is described in a Tcl script.…”

Section: Background and Related Workmentioning

confidence: 99%

“…To be specific, NS-2 simulator 6 uses (e.g. the literature [16][17][18][19] ) a Tcl script to connect all WSN sensors where each sensor is modeled as NS-2 node. J-Sim 7 is like NS-2 (e.g.…”

Section: Background and Related Workmentioning

confidence: 99%

“…The following summarizes a few examples of NS-2based WSN simulation. [16][17][18][19] Those models focused on routing protocols, data transmission, and their effect on energy consumption. The work in Shemim and Witkowski 16 studies various routing protocols effect on energy consumption using NS-2 simulator like Adaptive Clustering Hierarchy protocol (LEACH) 17 and Fuzzy-based routing protocols.…”

Section: Background and Related Workmentioning

confidence: 99%

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A grid-shaped cellular modeling approach for wireless sensor networks

Al-Zoubi

Wainer

2022

SIMULATION

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WSN (Wireless Sensor Network) applications have been widely used in recent years. We introduce a new method for modeling WSN, based on the specification of the WSN using the Cell-Discrete-Event Systems Specification (DEVS) formalism: the space is partitioned into cells where each cell can be considered a sensor, an obstacle, or anything of a behavior with defined rules. This model is then converted automatically into DEVS model at runtime. We present two case studies analyzing the use of energy in WSN member nodes, which have impact on prolonging the overall network lifetime. We study to analyze energy consumption related to routing and data transmission at the node level, and topology residual energy control methods at the cluster level (i.e. group of sensors) level. The goal is to show how these spatial modeling methods can be used for building WSN models in a simple but efficient fashion.

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Section: Background and Related Workmentioning

confidence: 99%

“…To be specific, NS-2 simulator 6 uses (e.g. the literature [16][17][18][19] ) a Tcl script to connect all WSN sensors where each sensor is modeled as NS-2 node. J-Sim 7 is like NS-2 (e.g.…”

Section: Background and Related Workmentioning

confidence: 99%

Section: Background and Related Workmentioning

confidence: 99%

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A grid-shaped cellular modeling approach for wireless sensor networks

Al-Zoubi

Wainer

2022

SIMULATION

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“…In fuzzy membership function based on the triangular and trapezoidal membership functions from [26][27] that are employed in the FIS to display input parameters are provided in Equations ( 9) and ( 10) respectively. The Mamdani Fuzzy inference system is used in this work.…”

Section: ) Fuzzy Membership Functionsmentioning

confidence: 99%

A Novel Energy Aware Clustering Mechanism with Fuzzy Logic in MANET Environment

Prasad¹,

Vuyyuru²,

Sushma³

et al. 2022

IJRITCC

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A Mobile Ad Hoc Networks (MANETs) comprises of the vast range of devices such as sensors, smart phones, laptops and other mobile devices that connect with each other across wireless networks and collaborate in a dispersed fashion to offer network functions in the absence of a permanent infrastructure. The Cluster Head (CH) selection in a clustered MANET is still crucial for lowering each node's energy consumption and increasing the network's lifetime. However, in existing clustering mechanism trust of the all nodes are presumed those causes increased challenge in the MANET environment. Security is a crucial factor when constructing ad-hoc networks. In a MANET, energy consumption in route optimization is dependent on network resilience and connectivity. The primary objective of this study is to design a reliable clustering mechanism for MANETs that takes energy efficiency into account. For trusted energy-efficient CH in the nodes, a safe clustering strategy integrating energy-efficient and fuzzy logic based energy clustering is proposed to address security problems brought about by malicious nodes and to pick a trustworthy node as CH. To improve the problem findings Bat algorithm (BAT) is integrated with Particle Swarm Optimization (PSO). The PSO technique is inspired because it imitates the sociological characteristics of the flock of the birds through random population. The BAT is a metaheuristic algorithm inspired by microbat echolocation behavior that uses pulse average with global optimization of the average path in the network. Hybrid Particle Swarm Optimization (HPSO) and BAT techniques are applied to identify the best route between the source and destination. According to the simulation results, the suggested Fuzzy logic Particle Swarm Optimization BAT (FLPSO-BAT) technique has a minimum latency of 0.0019 milliseconds, with energy consumption value of 0.09 millijoules, maximal throughput of 0.76 bits per sec and detection rate of 90.5% without packet dropping attack.

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A Fuzzy Based Clustering Approach to Prolong the Network Lifetime in Wireless Sensor Networks

Al-Hussain

Al–Suhail

2022

Intelligent Computing &Amp; Optimization

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Fuzzy Logic Approach for Cluster-Head Election in Wireless Sensor Network

Cited by 6 publications

References 11 publications

A grid-shaped cellular modeling approach for wireless sensor networks

A grid-shaped cellular modeling approach for wireless sensor networks

A Novel Energy Aware Clustering Mechanism with Fuzzy Logic in MANET Environment

A Fuzzy Based Clustering Approach to Prolong the Network Lifetime in Wireless Sensor Networks

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