Improvement of amorphous localization algorithm in WSN using ALO and GWO

Abstract

SummaryThe process of node identification is referred to as localization, and it is rapidly gaining popularity in the field of WSN. Different node identification processes have different findings, benefits, challenges, costs, effectiveness, and applications. In this work, the position error of the Amorphous algorithm is minimized by optimizing the hop size. For optimization of the hop size of the Amorphous algorithm, two different optimization algorithms, such as ALO and GWO, are considered. Proposed Amorphous‐ALO and Amorphous‐GWO provide higher accuracy rates of 33.89% and 4.22% than traditional Amorphous as well as ensemble approaches. Amorphous‐ALO and Amorphous‐GWO provide position errors 2.9161 and 2.9164 respectively, which are very similar. Therefore, to determine the suitable optimization algorithm for Amorphous, the minimum, average, and maximum execution times of Amorphous‐ALO and Amorphous‐GWO are considered. The approach that has less execution time is considered as most suitable for Amorphous. Amorphous‐ALO takes 67.76, 69.60 and 84.24 s for minimum, average and maximum execution whereas Amorphous‐GWO takes 65.17, 65.46 and 65.66 s for minimum, average and maximum execution respectively. As Amorphous‐GWO takes less execution time than Amorphous‐ALO; therefore, GWO is more suitable for optimization in Amorphous algorithm.