PATANLS: Performance Analysis of Trust-Aware Node Localization in WSNs

Finding the spatial coordinate of any unknown node using anchor nodes is Node Localization (NL). Anchor nodes (AN s) are GPS-enabled and know their locations. A malicious node (MN) may be involved in the localization process. So, Trust in the anchor nodes is essential for secure and reliable localization. A novel Sybil-free (SF) RSSI-based security scheme (P ATANLS) is proposed to unravel the issues of Sybil attacks in localization schemes. The proposed scheme requires nominal overhead for the devices and works efficiently based on the received signal. P ATANLS employs a trust-based technique to precisely determine the location of target nodes while limiting the influence of compromised or malevolent nodes on localization accuracy. The highly trustworthy AN s are later identified as legitimate nodes for the localization process. The paper addresses the limitations of existing localization approaches in WSNs. To further enhance the localization performance, the Coati Optimization Algorithm (COA) is designed by incorporating appropriate fitness functions. The performance of COA is then evaluated by comparing it with the butterfly optimization algorithm (BOA) and particle swarm optimization (PSO). The simulations are conducted utilizing the COA (Coati Optimization Algorithm), BOA (Butterfly Optimization Algorithm), and PSO (Particle Swarm Optimization). The comparative analysis of the COA, BOA, and PSO reveals that the COA surpasses the other algorithms in terms of node localization, node localization calculation time, and node localization error.