ABSTRACT
Planning and deploying a functional large scale Wireless Sensor Network (WSN) or a Network of Internet of Things (IoTs) is a challenging task, especially in complex urban environments. The typical complex urban environment distorts the RF signal from nodes due to multipath and as a result the connectivity of the network could be problematic. The need for accurate and reliable network simulators is mandatory to extract meaningful results. The fact that existing network layer simulators are unable to accurately simulate the physical layer effects, renders them inefficient to provide those results. In this work, we experimentally measure the signal strength of Crossbow TelosB node in different setups. The observations indicate that the actual behaviour of wireless nodes is highly variable and bimodal. Such an outcome stipulates the need of utilizing effective cross-layer simulators that can incorporate the physical layer conditions, in order to accurately simulate the performance of IoT networks in a complex urban environment.
- 2019. MICAZ node Datasheet. http://www.memsic.com/userfiles/files/Datasheets/WSN/micaz_datasheet-t.pdfGoogle Scholar
- Giacomo Brambilla, Marco Picone, Simone Cirani, Michele Amoretti, and Francesco Zanichelli. 2014. A Simulation Platform for Large-scale Internet of Things Scenarios in Urban Environments. In Proceedings of the First International Conference on IoT in Urban Space (URB-IOT '14). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), ICST, Brussels, Belgium, Belgium, 50--55. Google ScholarDigital Library
- Mihal Brumbulli and Emmanuel Gaudin. 2016. Towards Model-Driven Simulation of the Internet of Things. In Advances in Intelligent Systems and Computing. Springer International Publishing, 17--29. Google ScholarCross Ref
- G. D'Angelo, S. Ferretti, and V. Ghini. 2016. Simulation of the Internet of Things. In 2016 International Conference on High Performance Computing Simulation (HPCS). 1--8. Google ScholarCross Ref
- Xingjian Ding, Guodong Sun, Gaoxiang Yang, and Xinna Shang. 2016. Link Investigation of IEEE 802.15.4 Wireless Sensor Networks in Forests. Sensors 16, 7 (2016). Google ScholarCross Ref
- Dongjin Son, B. Krishnamachari, and J. Heidemann. 2004. Experimental study of the effects of transmission power control and blacklisting in wireless sensor networks. In 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004. 289--298. Google ScholarCross Ref
- Fractal Networx Limited. 2017. TruNET wireless, www.fractalnetworx.com.Google Scholar
- Alexander Gluhak, Srdjan Krco, Michele Nati, Dennis Pfisterer, Nathalie Mitton, and Tahiry Razafindralambo. 2011. A survey on facilities for experimental internet of things research. IEEE Communications Magazine 49, 11 (2011), 58--67. Google Scholar
- Ngoc Son Han, Gyu Myoung Lee, Noel Crespi, Nguyen Van Luong, Kyongwoo Heo, Mihaela Brut, and Patrick GATELLIER. 2014. DPWSim: A simulation toolkit for IoT applications using devices profile for web services. In 2014 IEEE World Forum on Internet of Things (WF-IoT). Seoul, South Korea, 544--547. Google ScholarCross Ref
- Loizos Kanaris, Akis Kokkinis, Giancarlo Fortino, Antonio Liotta, and Stavros Stavrou. 2016. Sample Size Determination Algorithm for fingerprint-based indoor localization systems. Computer Networks 101 (2016), 169--177. Google ScholarDigital Library
- Loizos Kanaris, Charalampos Sergiou, Akis Kokkinis, Aris Pafitis, Nikos Antoniou, and Stavros Stavrou. 2019. On the Realistic Radio and Network Planning of IoT Sensor Networks. Sensors 19, 15 (2019). Google ScholarCross Ref
- D. Rojas and J. Barrett. 2016. Experimental Analysis of a Wireless Sensor Network in a Multi-Chamber Metal Environment. In European Wireless 2016; 22th European Wireless Conference. 1--6.Google Scholar
- Weisheng Tang, Xiaoyuan Ma, Jianming Wei, and Zhi Wang. 2019. Measurement and Analysis of Near-Ground Propagation Models under Different Terrains for Wireless Sensor Networks. Sensors 19, 8 (2019). Google ScholarCross Ref
- Y. M. Yusof, A. K. M. M. Islam, and S. Baharun. 2015. An experimental study of WSN transmission power optimisation using MICAz motes. In 2015 International Conference on Advances in Electrical Engineering (ICAEE). 182--185. Google ScholarCross Ref
- An experimental study of IoT transmission power, in outdoor environment, using Crossbow TelosB nodes
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