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Clustering and Compressive Data Gathering for Transmission Efficient Wireless Sensor Networks
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Author(s): Utkarsha Sumedh Pacharaney (Datta Meghe College of Engineering, India), Ranjan Bala Jain (Vivekanand Education Society's Institute of Technology, India)and Rajiv Kumar Gupta (Terna Engineering College, University of Mumbai, India)
Copyright: 2021
Pages: 28
Source title:
Managing Resources for Futuristic Wireless Networks
Source Author(s)/Editor(s): Mamata Rath (Birla School of Management, Birla Global University, India)
DOI: 10.4018/978-1-5225-9493-2.ch002
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Abstract
The chapter focuses on minimizing the amount of wireless transmission in sensory data gathering for correlated data field monitoring in wireless sensor networks (WSN), which is a major source of power consumption. Compressive sensing (CS) is a new in-node compression technique that is economically used for data gathering in an energy-constrained WSN. Among existing CS-based routing, cluster-based methods offer the most transmission-efficient architecture. Most CS-based clustering methods randomly choose nodes to form clusters, neglecting the topology structure. A novel base station (BS)-assisted cluster, spatially correlated cluster using compressive sensing (SCC_CS), is proposed to reduce number of transmissions in and form the cluster by exploiting spatial correlation based on geographical proximity. The proposed BS-assisted clustering scheme follows hexagonal deployment strategy. In SCC_CS, cluster heads are solely involved in data gathering and transmitting CS measurements to BS, saving intra-cluster communication cost, and thus, network life increases as proved by simulation.
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