2019Journal of Intelligent & Fuzzy SystemsRequires access

An intelligent energy efficient clustering technique for multiple base stations positioning in a wireless sensor network

Veervrat Singh Chandrawanshi, Rajiv Kumar Tripathi, Rahul Pachauri

Open publisher page 8 citations

Abstract

A wireless sensor network consists of a large number of sensor nodes. The key parameters of the wireless sensor network are limited energy, network lifetime, limited ability, secure communication, quality of service, data aggregation, and synchronization. In wireless sensor network when the single base station multi-hop communication model is used, the adjacent nodes to the base station transmitted all the data to the base station. Thus the adjacent nodes deplete their energy earlier than other nodes and create the energy holes near the base station. These energy holes minimize the lifetime of the network. The primary objective in large-scale wireless sensor networks is to increase the lifetime with limited energy resources. This can be achieved by placing the multiple base stations using an intelligent clustering technique in a wireless sensor network. In this paper, an intelligent clustering technique has been proposed to choose the optimal position of multiple base stations with the help of k-means++ clustering technique in conjunction with the local+ scheme. The simulation result shows that the proposed method provides minimum energy consumption with an extended lifetime in comparison to the two individual clustering techniques.

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What this paper is about

A wireless sensor network consists of a large number of sensor nodes. The key parameters of the wireless sensor network are limited energy, network lifetime, limited ability, secure communication, quality of service, data aggregation, and synchronization. In wireless sensor network when the single base station multi-hop communication model is used, the adjacent nodes to the base station transmitted all the data to the base station. Thus the adjacent nodes deplete their energy earlier than other nodes and create the energy holes near the base station. These energy holes minimize the lifetime of the network. The primary objective in large-scale wireless sensor networks is to increase the lifetime with limited energy resources. This can be achieved by placing the multiple base stations using an intelligent clustering technique in a wireless sensor network. In this paper, an intelligent clustering technique has been proposed to choose the optimal position of multiple base stations with the help of k-means++ clustering technique in conjunction with the local+ scheme. The simulation result shows that the proposed method provides minimum energy consumption with an extended lifetime in comparison to the two individual clustering techniques.

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Available abstract

A wireless sensor network consists of a large number of sensor nodes. The key parameters of the wireless sensor network are limited energy, network lifetime, limited ability, secure communication, quality of service, data aggregation, and synchronization. In wireless sensor network when the single base station multi-hop communication model is used, the adjacent nodes to the base station transmitted all the data to the base station. Thus the adjacent nodes deplete their energy earlier than other nodes and create the energy holes near the base station. These energy holes minimize the lifetime of the network. The primary objective in large-scale wireless sensor networks is to increase the lifetime with limited energy resources. This can be achieved by placing the multiple base stations using an intelligent clustering technique in a wireless sensor network. In this paper, an intelligent clustering technique has been proposed to choose the optimal position of multiple base stations with the help of k-means++ clustering technique in conjunction with the local+ scheme. The simulation result shows that the proposed method provides minimum energy consumption with an extended lifetime in comparison to the two individual clustering techniques.

Key concepts: Base station, Wireless sensor network, Key distribution in wireless sensor networks, Computer science, Cluster analysis, Computer network, Base transceiver station, Energy consumption

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