期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2022
卷号：12
期号：1
页码：660-668
DOI：10.11591/ijece.v12i1.pp660-668
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Wireless networks are currently used in a wide range of healthcare, military, or environmental applications. Wireless networks contain many nodes and sensors that have many limitations, including limited power, limited processing, and narrow range. Therefore, determining the coordinates of the location of a node of the unknown location at a low cost and a limited treatment is one of the most important challenges facing this field. There are many meta-heuristic algorithms that help in identifying unknown nodes for some known nodes. In this manuscript, hybrid metaheuristic optimization algorithms such as grey wolf optimization and salp swarm algorithm are used to solve localization problem of internet of things (IoT) sensors. Several experiments are conducted on every meta-heuristic optimization algorithm to compare them with the proposed method. The proposed algorithm achieved high accuracy with low error rate (0.001) and low power consumption.
