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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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