Authors:
R. Regin, S. Silvia Priscila, Gnaneswari Gnanaguru, T. Shynu, M. Sakthivanitha

Addresses:
Department of Computer Science Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, Tamil Nadu, India. Department of Computer Science, Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India. Department of Computer Applications, CMR Institute of Technology, Marathahalli, Bengaluru, Karnataka, India. Department of Research and Development, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India. Department of Information Technology, Vels Institute of Science Technology and Advance Studies, Chennai, Tamil Nadu, India.

Abstract:

Extending a network’s lifetime has always been a tough problem in WSNs. Several new methods have been proposed recently to address this issue of extending network lifetime for WSNs in various fields. In this paper, survey papers provide a comprehensive analysis of energy-efficient approaches utilized for target coverage solutions in WSN with numerous sensing units to enhance network lifetime. This paper examines the comprehensive review of documents that suggested ACO, D-UREA, and a scheduling algorithm. A promising performance is demonstrated in the review paper on optimization technique, i.e., ant colony optimization, which improves energy efficiency in the WSNs. The network coverage maximization in the random deployment of the sensor node network is examined and analyzed by the review paper on the Distributed Uncovered Region Exploration Algorithm, which adopts a distributed self-organizing deployment approach. Finally, an answer to extended network lifetime is discussed by the scheduling algorithm paper regarding the MTC issue over the WSN, in which transmitting power and overlapped targets are also considered. The simulation results of the given review papers are also graphically depicted and discussed, as well as their performances.

Keywords: Wireless Sensor Networks (WSNs); Network Coverage; Multiple-Target Coverage (MTC); ACO Algorithm; Distributed-Uncovered Region Exploration Algorithm (D-UREA); Battery Depletion; Data Aggregation.

Received on: 19/05/2024, Revised on: 03/07/2024, Accepted on: 07/09/2024, Published on: 03/12/2024

DOI: 10.69888/FTSCL.2024.000280

FMDB Transactions on Sustainable Computer Letters, 2024 Vol. 2 No. 4, Pages: 207-216

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