Abstract:
Wireless networks include a set of nodes which are connected to one another via wireless links for communication purposes.
Wireless sensor networks (WSN) are a type of wireless network, which utilizes sensor nodes to collect and communicate data.
Node localization is a challenging problem in WSN which intends to determine the geographical coordinates of the sensors in
WSN. It can be considered an optimization problem and can be addressed via metaheuristic algorithms. This study introduces
an elite oppositional farmland fertility optimization-based node localization method for radio communication networks, called
EOFFO-NLWN technique. It is the goal of the proposed EOFFO-NLWN technique to locate unknown nodes in the network
by using anchor nodes as a starting point. As a result of merging the principles of elite oppositional-based learning (EOBL)
and the agricultural fertility optimization algorithm (FFO), we have developed the EOFFO-NLWN approach, which is
described in detail below. The EOBL concept makes it easier to populate the FFO algorithm’s population initialization, which
results in an increase in the exploration rate. Various BNs and CRs were tested, and the findings revealed that the EOFFO NLWN technique outperformed all other known techniques in all cases. A comprehensive experimental result analysis of the
EOFFO-NLWN technique is performed under several measures, and the results described the sovereignty of the EOFFO NLWN method associated to existing techniques.
