Secure and optimal localization of wireless sensor networks

Abstract

A wireless sensor network consists of battery-operated sensor nodes newlineused for various real-time applications like agriculture, environmental newlinemonitoring, surveillance, robot vision, and target tracking. Localization is an newlineimportant process in WSN for finding the location of nodes, especially, where newlinethere is no Global Positioning Systems (GPSs) data is not available. Localization newlineis the initial process for other network functionalities such as routing, clustering newlineand data aggregation. Due to economic constrain also installation of GPS is not newlineconceivable in all sensor devices. This work attempts to propose a new newlinelocalization technique using soft computing and optimization algorithms. newlineWhen localizing WSNs, calculating the distances of sensor nodes newlinebased on the known locations of the anchor nodes is a difficult task. For an newlineaccurate localization, the exact distance calculation of the node is necessary. newlineIn this work, AI algorithm of Adaptive Neural Fuzzy Inference System (ANFIS) newlineis used for localization in WSN. This ANFIS is the combination of both the newlineFuzzy Logic (FL) and the Neural Network (NN) which is highly efficient and newlineaccurate than prior methods. The RSSI of anchor nodes are utilized as basic newlineparameter to evaluate the location of SN. Whereas the ANFIS perform newline