Optimized Anchor based Localization using Bat Optimization Algorithm for Heterogeneous WSN

Abstract

Sensor node localization refers to the knowledge of position information and is a procedural technique for estimating sensor node location. In wireless sensor networks, localization refers to the estimation of sensor node location information. Optimization algorithms are used to determine the position of sensor nodes. Traditional algorithms rely on analytical methods, which increase in computational complexity as the number of sensor nodes grows. Due to resource constraints, cost constraints, and sensor node energy constraints, an algorithm with reduced computational complexity is needed, one that does not need external hardware, needs less run time and memory, is scalable and easy to implement without losing performance, and has improved location estimation accuracy with better convergence. In order to meet these objectives, the proposed to design an optimization technique based on Bat Optimization Algorithm. For each unknown or non-localized node, the algorithm estimates at least 3 reference nodes based on the parameters. Through result it has been proved that this method reduces localization error and delay time and gives better accuracy. Another Important research contribution is this Heterogeneous Wireless Sensor Network (HWSN) utilizes the Natural Language Processing for the performance metric improvement. This HWSN that uses the data in native natural languages processing for localizing speech communication sources and to locate the nodes themselves in the HWSN. Here, performance metrics measured by Time of Arrival and Speed ranging of the nodes from the Speech Acoustic Communication.