scholarly journals A Genetic Algorithm-Based Approach for Energy- Efficient Clustering of Wireless Sensor Networks

2012 ◽  
Author(s):  
A. Zahmatkesh
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Energy Efficient Clustering

A Novel Energy-Efficient Clustering Protocol Using Two-Stage Genetic Algorithm for Improving the Lifetime of Wireless Sensor Networks

2020 ◽  
Vol 19 (03) ◽  
pp. 2050019
Author(s):  
Ali Mahani ◽  
Ebrahim Farahmand ◽  
Saeide Sheikhpour ◽  
Nooshin Taheri-Chatrudi
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Clustering Protocol ◽  
New Energy ◽  
Energy Efficient Clustering

Wireless sensor networks (WSNs) are beginning to be deployed at an accelerated pace, and they have attracted significant attention in a broad spectrum of applications. WSNs encompass a large number of sensor nodes enabling a base station (BS) to sense and transmit data over the area where WSN is spread. As most sensor nodes have a limited energy capacity and at the same time transmit critical information, enhancing the lifetime and the reliability of WSNs are essential factors in designing these networks. Among many approaches, clustering of sensor nodes has proved to be an effective method of reducing energy consumption and increasing lifetime of WSNs. In this paper, a new energy-efficient clustering protocol is implemented using a two-step Genetic Algorithm (GA). In the first step of GA, cluster heads (CHs) are selected, and in the second step, cluster members are chosen based on their distance to the selected CHs. Compared to other clustering protocols, the lifetime of WSNs in the proposed clustering is improved. This improvement is the consequence of the fact that this clustering considers energy efficient parameters in clustering protocol.

scholarly journals GAECH: Genetic Algorithm Based Energy Efficient Clustering Hierarchy in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
B. Baranidharan ◽  
B. Santhi
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Fitness Function ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
The Stability ◽  
Energy Efficient Clustering

Clustering the Wireless Sensor Networks (WSNs) is the major issue which determines the lifetime of the network. The parameters chosen for clustering should be appropriate to form the clusters according to the need of the applications. Some of the well-known clustering techniques in WSN are designed only to reduce overall energy consumption in the network and increase the network lifetime. These algorithms achieve increased lifetime, but at the cost of overloading individual sensor nodes. Load balancing among the nodes in the network is also equally important in achieving increased lifetime. First Node Die (FND), Half Node Die (HND), and Last Node Die (LND) are the different metrics for analysing lifetime of the network. In this paper, a new clustering algorithm, Genetic Algorithm based Energy efficient Clustering Hierarchy (GAECH) algorithm, is proposed to increase FND, HND, and LND with a novel fitness function. The fitness function in GAECH forms well-balanced clusters considering the core parameters of a cluster, which again increases both the stability period and lifetime of the network. The experimental results also clearly indicate better performance of GAECH over other algorithms in all the necessary aspects.

Genetic algorithm for energy-efficient clustering and routing in wireless sensor networks

2018 ◽  
Vol 146 ◽  
pp. 196-214 ◽  
Author(s):  
Tianshu Wang ◽  
Gongxuan Zhang ◽  
Xichen Yang ◽  
Ahmadreza Vajdi
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Energy Efficient Clustering
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