• NITHIN V
• VISHNU RAAJ A
• NAVEEN KUMAR A

The bulk of the earth's surface is expected to be covered by wireless sensor networks (WSN). In the Internet of Things era, the WSN is the principal data collecting framework. The research community has offered a number of solutions to deal with the energy efficient data collection paradigm in WSN. The standard DSR protocol is investigated in this study in order to improve the operating efficiency and service life of wireless sensor networks. This study proposes a clustering method based on the K-means algorithm. To maximize network coverage and reduce energy consumption while maintaining quality of service, a wireless sensor network coverage optimization solution based on an upgraded artificial fish swarm algorithm was proposed. A controlled experiment will also be carried out to assess the suggested algorithm's effectiveness and practical implications. The results show that the method suggested in this paper has some advantages over other methods and can be used as a theoretical foundation for future study in this field.

Wireless sensor network, coverage optimization, fish swarm algorithm, reverse learning, k – means clustering.

"Network Coverage OPtimizaton Using Artificial Fish Swarm Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.i93-i99, May-2022, Available :http://www.jetir.org/papers/JETIR2205912.pdf

"Network Coverage OPtimizaton Using Artificial Fish Swarm Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppi93-i99, May-2022, Available at : http://www.jetir.org/papers/JETIR2205912.pdf