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Article

Simulation Tool for the Analysis of Cooperative Localization Algorithms for Wireless Sensor Networks

1
Department of Mechanical Engineering, University of Cordoba, Campus de Rabanales, 14071 Cordoba, Spain
2
Department of Computer Science and Numerical Analysis, University of Cordoba, Campus de Rabanales, 14071 Cordoba, Spain
3
Department of Communications and Networking, School of Electrical Engineering, Aalto University, FI-00076 Aalto, Finland
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(13), 2866; https://doi.org/10.3390/s19132866
Received: 31 May 2019 / Revised: 21 June 2019 / Accepted: 26 June 2019 / Published: 27 June 2019
(This article belongs to the Special Issue Sensor Data Fusion for IoT and Industrial Applications)
Within the context of the Internet of Things (IoT) and the Location of Things (LoT) service, this paper presents an interactive tool to quantitatively analyze the performance of cooperative localization techniques for wireless sensor networks (WSNs). In these types of algorithms, nodes help each other determine their location based on some signal metrics such as time of arrival (TOA), received signal strength (RSS), or a fusion of them. The developed tool is intended to provide researchers and designers a fast way to measure the performance of localization algorithms considering specific network topologies. Using TOA or RSS models, the Crámer-Rao lower bound (CRLB) has been implemented within the tool. This lower bound can be used as a benchmark for testing a particular algorithm for specific channel characteristics and WSN topology, which allows determination if the necessary accuracy for a specific application is possible. Furthermore, the tool allows us to consider independent characteristics for each node in the WSN. This feature allows the avoidance of the typical “disk graph model,” which is usually applied to test cooperative localization algorithms. The tool allows us to run Monte-Carlo simulations and generate statistical reports. A set of basic illustrative examples are described comparing the performance of different localization algorithms and showing the capabilities of the presented tool. View Full-Text
Keywords: algorithms; indoor localization; cooperative localization; industrial safety; IoT; LoT algorithms; indoor localization; cooperative localization; industrial safety; IoT; LoT
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MDPI and ACS Style

Ruz, M.L.; Garrido, J.; Jiménez, J.; Virrankoski, R.; Vázquez, F. Simulation Tool for the Analysis of Cooperative Localization Algorithms for Wireless Sensor Networks. Sensors 2019, 19, 2866. https://doi.org/10.3390/s19132866

AMA Style

Ruz ML, Garrido J, Jiménez J, Virrankoski R, Vázquez F. Simulation Tool for the Analysis of Cooperative Localization Algorithms for Wireless Sensor Networks. Sensors. 2019; 19(13):2866. https://doi.org/10.3390/s19132866

Chicago/Turabian Style

Ruz, Mario L., Juan Garrido, Jorge Jiménez, Reino Virrankoski, and Francisco Vázquez. 2019. "Simulation Tool for the Analysis of Cooperative Localization Algorithms for Wireless Sensor Networks" Sensors 19, no. 13: 2866. https://doi.org/10.3390/s19132866

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