Clustering Algorithm Using Bayes’ Rule in Mobile Wireless Sensor Networks

Author(s):  
Young-Bae Kong ◽  
Kyung-Bae Chang ◽  
Gwi-Tae Park
Author(s):  
Amine Dahane ◽  
Nasr-Eddine Berrached ◽  
Abdelhamid Loukil

Clustering approaches for mobile wireless sensor networks (WSNs) tend to extend the battery life of the individual sensors and the network lifetime. Taking into account the mobility of the network, a powerful mechanism to safely elect a cluster head is a challenging task in many research works. As a proposed technique to deal with such problem, the approach based on the computing of the weight of each node in the network is chosen. This paper is intended to propose a new algorithm called “S-WCA” for safety of mobile sensor networks based on clustering algorithm using a combination of five metrics. Among these metrics lies the behavioral level metric which promotes a safe choice of a cluster head in the sense where this last one will never be a malicious node. Moreover, a summary of the highlight of the authors' work is provided in a comprehensive strategy for monitoring the network, so as to detect and remove the malicious nodes. Simulation study is used to demonstrate the performance of the proposed algorithm.


2020 ◽  
pp. 1302-1331
Author(s):  
Amine Dahane ◽  
Nasr-Eddine Berrached ◽  
Abdelhamid Loukil

Clustering approaches for mobile wireless sensor networks (WSNs) tend to extend the battery life of the individual sensors and the network lifetime. Taking into account the mobility of the network, a powerful mechanism to safely elect a cluster head is a challenging task in many research works. As a proposed technique to deal with such problem, the approach based on the computing of the weight of each node in the network is chosen. This paper is intended to propose a new algorithm called “S-WCA” for safety of mobile sensor networks based on clustering algorithm using a combination of five metrics. Among these metrics lies the behavioral level metric which promotes a safe choice of a cluster head in the sense where this last one will never be a malicious node. Moreover, a summary of the highlight of the authors' work is provided in a comprehensive strategy for monitoring the network, so as to detect and remove the malicious nodes. Simulation study is used to demonstrate the performance of the proposed algorithm.


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