Increasing Energy Efficiency in Wireless Sensor Networks Using GA-ANFIS to Choose a Cluster Head and Assess Routing and Weighted Trusts to Demodulate Attacker Nodes

• Published in: Foundations of science Vol. 25; no. 4; pp. 1227 - 1246
• Main Authors: Al Hayali, Shaymaa, Rahebi, Javad, Ucan, Osman N., Bayat, Oguz
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.12.2020; Springer; Springer Nature B.V
• Subjects: Adaptive algorithms; Adaptive systems; Algorithms; Artificial neural networks; Clustering; Education; Energy; Energy efficiency; Energy management systems; Energy use; Fuzzy logic; Genetic algorithms; Life span; Mathematical Logic and Foundations; Methodology of the Social Sciences; Nodes; Packets (communication); Philosophy; Philosophy of Science; Sensors; Trustworthiness; Wireless networks; Wireless sensor networks; Canada; Wireless sensor network; LEACH; Fuzzy; Adaptive neuro-fuzzy inference system; Genetic algorithm

Demodulating harmful nodes and diminishing the energy waste in sensor nodes can prolong the lifespan of wireless sensor networks (WSNs). In this study, a genetic algorithm (GA) and an adaptive neuro fuzzy inference system were used to diminish the energy waste of sensors. Weighted trust evaluation w...