Standard deviation based weighted clustering algorithm for wireless sensor networks

2016 ◽  
Author(s):  
Faris AL-Baadani ◽  
Sufian Yousef ◽  
Laith AL-Jabouri ◽  
Sourabh Bhart
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Standard Deviation ◽  
Clustering Algorithm ◽  
Wireless Sensor ◽  
Weighted Clustering

scholarly journals Energy Efficient and Safe Weighted Clustering Algorithm for Mobile Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Amine Dahane ◽  
Abdelhamid Loukil ◽  
Bouabdellah Kechar ◽  
Nasr-Eddine Berrached
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Mobile Wireless ◽  
Mobile Wireless Sensor Networks ◽  
Weighted Clustering ◽  
Mobile Wireless Sensor

The main concern of clustering approaches for mobile wireless sensor networks (WSNs) is to prolong the battery life of the individual sensors and the network lifetime. For a successful clustering approach the need of a powerful mechanism to safely elect a cluster head remains a challenging task in many research works that take into account the mobility of the network. The approach based on the computing of the weight of each node in the network is one of the proposed techniques to deal with this problem. In this paper, we propose an energy efficient and safe weighted clustering algorithm (ES-WCA) for mobile WSNs 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, the highlight of our work is summarized in a comprehensive strategy for monitoring the network, in order to detect and remove the malicious nodes. We use simulation study to demonstrate the performance of the proposed algorithm.

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