Sensor node localization using nature-inspired algorithms with fuzzy logic in WSNs

Abstract

The node localization problem of wireless sensor networks (WSNs) is addressed in this article with a node localization algorithm designed using fuzzy logic and a nature-inspired algorithm. The coordinates of target nodes are obtained using fuzzy logic reasoning and nature-inspired algorithms. The fuzzy logic concept is used to remove the nonlinearities that arise due to signal strength measurement in the process of range estimation. The triangular and trapezoidal membership functions are used with the Mamdani fuzzy inference system for distance improvement between sensor nodes. Further, particle swarm optimization (PSO) and the Jaya algorithm (JA) determine the target nodes’ location coordinates. The comparison of the proposed fuzzy logic-based PSO (FL-PSO) and fuzzy logic-based JA (FL-JA) algorithms is made with PSO and Jaya algorithm-based node localization algorithms for localization error. The influence of anchor nodes and degree of irregularity is verified during localization analysis on the FL-PSO and FL-JA node localization algorithms. The proposed FL-PSO and FL-JA node localization algorithms are evaluated for scalability, computation time, mean absolute deviation, and complexity to determine their efficacy. The simulations are carried out on MATLAB software in addition to the fuzzy logic toolbox.