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Mathematics 2019, 7(2), 184; https://doi.org/10.3390/math7020184

A Multi-Objective DV-Hop Localization Algorithm Based on NSGA-II in Internet of Things

1
Complex System and Computational Intelligent Laboratory, Taiyuan University of Science and Technology, Taiyuan 030024, China
2
School of Information, Beijing Wuzi University, Beijing 101149, China
3
Department of Computer Science and Software Engineering, Swinburne University of Technology, Melbourne 3000, Australia
*
Authors to whom correspondence should be addressed.
Received: 17 December 2018 / Revised: 6 February 2019 / Accepted: 7 February 2019 / Published: 15 February 2019
(This article belongs to the Special Issue Evolutionary Computation)
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Abstract

Locating node technology, as the most fundamental component of wireless sensor networks (WSNs) and internet of things (IoT), is a pivotal problem. Distance vector-hop technique (DV-Hop) is frequently used for location node estimation in WSN, but it has a poor estimation precision. In this paper, a multi-objective DV-Hop localization algorithm based on NSGA-II is designed, called NSGA-II-DV-Hop. In NSGA-II-DV-Hop, a new multi-objective model is constructed, and an enhanced constraint strategy is adopted based on all beacon nodes to enhance the DV-Hop positioning estimation precision, and test four new complex network topologies. Simulation results demonstrate that the precision performance of NSGA-II-DV-Hop significantly outperforms than other algorithms, such as CS-DV-Hop, OCS-LC-DV-Hop, and MODE-DV-Hop algorithms. View Full-Text
Keywords: wireless sensor networks (WSNs); DV-Hop algorithm; multi-objective DV-Hop localization algorithm; NSGA-II-DV-Hop wireless sensor networks (WSNs); DV-Hop algorithm; multi-objective DV-Hop localization algorithm; NSGA-II-DV-Hop
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Wang, P.; Xue, F.; Li, H.; Cui, Z.; Xie, L.; Chen, J. A Multi-Objective DV-Hop Localization Algorithm Based on NSGA-II in Internet of Things. Mathematics 2019, 7, 184.

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