A Novel Efficient Heuristic Based Localization Paradigm in Wireless Sensor Network

被引：0
作者：
P. Sruthi
K. Sahadevaiah
机构：
[1] CMR College of Engineering & Technology,Department of Computer Science and Engineering
[2] JNT University,Department of Computer Science and Engineering
来源：
Wireless Personal Communications | 2022年 / 127卷
关键词：
Wireless sensor; Network; Localization; Signal strength; Known and unknown nodes; Irregularity radio range; Time of arrival; Angle formation; Location tracking;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Wireless sensor network (WSN) is applicable in all IoT applications, thus it has many advancements. However, it has many drawbacks like localization, link failure, and so on. In addition, the reduction of received signal strength (RSS) often causes path loss, while transferring the data when the path is lost then it drops the packets. To address this problem, the current research aimed to develop a novel grey wolf ant lion recurrent (GWALR) localization model in WSN to find the location of each unknown node. Moreover, the fitness function of GWALR is utilized to track the location of each node. The key focus of this proposed model is to find the location of unknown nodes and to improve the RSS by reducing the localization error. In addition, the model that attained high RSS measure has better data broadcasting rate. Finally, the performance of the proposed approach is compared with existing works and attained better accuracy and reduced error rate. Thus the outcome of the proposed model proved the efficiency of the proposed work by gaining maximum throughput ratio as 7000bps, data broadcasting rate as 99%, accuracy 99.8% and reduced error rate as 1.4%.
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页码：63 / 83
页数：20
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