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Link quality evaluation of a wireless sensor network in metal marine environments

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Abstract

Wireless sensor networks (WSN) are finding increasing use in all-metal marine environments such as ships, oil and gas rigs, freight container terminals, and marine energy platforms. However, wireless propagation in an all-metal environment with ducting and sealed doors between compartments is difficult to model, and the operating machinery further complicates wireless network planning. This makes it necessary to characterize the performance of the physical wireless links in the actual operating environments. However, little has been reported in the literature on methodologies for measuring the full range of physical link quality indicators. In this paper, we present a methodology for doing this that we have verified by the deployment of a 2.4 GHz network of 18 nodes in three different all-metal scenarios: a cluster of freight containers, a full-sized shore-based working ship’s engine room training facility, and an operational ship’s engine room. The output variables included the key link quality indicators of packet delivery ratio (PDR), RSSI, and LQI for every possible link, as well as the performance of every node. We believe that this is the first time that this full range of physical link quality indicators has been measured in this type of application environment. We found that in all three scenarios the network performed with over 90% PDR average. However, as the scenarios become more complex, the communications become more unpredictable, yielding a wider transition zone, indicating that although a WSN could operate in these scenarios under different conditions, a pre-deployment practical study is essential for each new scenario.

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References

  1. Alemdar, H., & Ersoy, C. (2010). Wireless sensor networks for healthcare: A survey. Computer Networks, 54(15), 2688–2710.

    Article  Google Scholar 

  2. Aygün, B., & Cagri Gungor, V. (2011). Wireless sensor networks for structure health monitoring: Recent advances and future research directions. Sensor Review, 31(3), 261–276.

    Article  Google Scholar 

  3. Baccour, N., Koubâa, A., Mottola, L., Zúñiga, M. A., Youssef, H., Boano, C. A., et al. (2012). Radio link quality estimation in wireless sensor networks: A survey. ACM Transactions on Sensor Networks (TOSN), 8(4), 34.

    Article  Google Scholar 

  4. Bertocco, M., Gamba, G., & Sona, A. (2008). Assessment of out-of-channel interference effects on IEEE 802.15. 4 wireless sensor networks. In Instrumentation and measurement technology conference proceedings, 2008. IMTC 2008 (pp. 1712–1717). IEEE.

  5. Boano, C. A., Römer, K., & Tsiftes, N. (2014). Mitigating the adverse effects of temperature on low-power wireless protocols. In 2014 IEEE 11th international conference on mobile ad hoc and sensor systems (MASS) (pp. 336–344). IEEE.

  6. Ceriotti, M., Chini, M., Murphy, A.L., Picco, G.P., Cagnacci, F., & Tolhurst, B. (2010). Motes in the jungle: Lessons learned from a short-term WSN deployment in the Ecuador cloud forest. In Real-world wireless sensor networks (pp. 25–36). Berlin: Springer.

  7. Ferens, K., Woo, L., & Kinsner, W. (2009). Performance of zigbee networks in the presence of broadband electromagnetic noise. In CCECE’09. Canadian conference on electrical and computer engineering, 2009 (pp. 407–410). IEEE.

  8. Fundation, H. C. (2006). Hart field communication protocol specification. HFC_SPEC12, Revision 6.

  9. Ganesan, D., Krishnamachari, B., Woo, A., Culler, D., Estrin, D., & Wicker, S. (2002). Complex behavior at scale: An experimental study of low-power wireless sensor networks. Technical report, Citeseer.

  10. Istomin, T., Marfievici, R., Murphy, A. L., & Picco, G. P. (2014). Trident: In-field connectivity assessment for wireless sensor networks. In Proceedings of the 6th extreme conference on communication and computing (ExtremeCom).

  11. Kdouh, H., Zaharia, G., Brousseau, C., El Zein, G., & Grunfelder, G. (2011). Zigbee-based sensor network for shipboard environments. In 2011 10th international symposium on signals, circuits and systems (ISSCS) (pp. 1–4). IEEE.

  12. Kdouh, H., Brousseau, C., Zaharia, G., Grunfeleder, G., & Zein, G. (2012). A realistic experiment of a wireless sensor network on board a vessel. In 2012 9th international conference on communications (COMM) (pp. 189–192). IEEE.

  13. Kdouh, H., Farhat, H., Zaharia, G., Brousseau, C., Grunfelder, G., & Zein, G. (2012). Performance analysis of a hierarchical shipboard wireless sensor network. In 2012 IEEE 23rd international symposium on personal indoor and mobile radio communications (PIMRC) (pp. 765–770). IEEE.

  14. Kdouh, H., Zaharia, G., Brousseau, C., Grunfelder, G., Farhat, H., & El Zein, G. (2012). Wireless sensor network on board vessels. In 2012 19th international conference on telecommunications (ICT) (pp. 1–6). IEEE.

  15. Marfievici, R., Murphy, A., Picco, G., Ossi, F., & Cagnacci, F. (2013). How environmental factors impact outdoor wireless sensor networks: A case study. In 2013 IEEE 10th international conference on mobile ad-hoc and sensor systems (MASS) (pp. 565–573). https://doi.org/10.1109/MASS.2013.13.

  16. Marfievici, R., Corbalán, P., Rojas, D., McGibney, A., Rea, S., & Pesch, D. (2017). Tales from the c130 horror room: A wireless sensor network story in a data center. In Proceedings of the first ACM international workshop on the engineering of reliable, robust, and secure embedded wireless sensing systems, ACM, New York, NY, USA, FAILSAFE’17 (pp. 24–31).

  17. Ovsthus, K., Kristensen, L. M., et al. (2014). An industrial perspective on wireless sensor networksa survey of requirements, protocols, and challenges. IEEE Communications Surveys & Tutorials, 16(3), 1391–1412.

    Article  Google Scholar 

  18. Pilsak, T., & ter Haseborg, J. L. (2010). Simulation of wireless sensor networks on vessels under consideration of EMC. In 2010 Asia-Pacific symposium on electromagnetic compatibility (APEMC) (pp. 602–605). IEEE.

  19. Polastre, J., Szewczyk, R., & Culler, D. (2005). Telos: enabling ultra-low power wireless research. In fourth international symposium on information processing in sensor networks, 2005. IPSN 2005 (pp. 364–369). IEEE.

  20. Rashid, B., & Rehmani, M. H. (2016). Applications of wireless sensor networks for urban areas: A survey. Journal of Network and Computer Applications, 60, 192–219.

    Article  Google Scholar 

  21. Rehmani, M. H., Rachedi, A., Lohier, S., Alves, T., & Poussot, B. (2014). Intelligent antenna selection decision in IEEE 802.15. 4 wireless sensor networks: An experimental analysis. Computers & Electrical Engineering, 40(2), 443–455.

    Article  Google Scholar 

  22. Rojas, D., & Barrett, J. (2016). Experimental analysis of a wireless sensor network in a multi-chamber metal environment. In: European wireless 2016; 22th European wireless conference; Proceedings of VDE (pp. 1–6).

  23. Rojas, D., & Barrett, J. (2017). A hardware–software WSN platform for machine and structural monitoring. In 2017 28th Irish signals and systems conference (ISSC) (pp. 1–6). IEEE.

  24. Rondinone, M., Ansari, J., Riihijärvi, J., & Mähönen, P. (2008). Designing a reliable and stable link quality metric for wireless sensor networks. In Proceedings of the workshop on real-world wireless sensor networks (pp. 6–10). ACM.

  25. Sexton, D., Mahony, M., Lapinski, M., & Werb, J. (2005). Radio channel quality in industrial wireless sensor networks. In Sensors for industry conference, 2005 (pp. 88–94). IEEE.

  26. Srinivasan, K., Dutta, P., Tavakoli, A., & Levis, P. (2010). An empirical study of low-power wireless. ACM Transactions on Sensor Networks (TOSN), 6(2), 16.

    Article  Google Scholar 

  27. Suryadevara, N. K., Mukhopadhyay, S. C., Kelly, S. D. T., & Gill, S. P. S. (2015). Wsn-based smart sensors and actuator for power management in intelligent buildings. IEEE/ASME Transactions on Mechatronics, 20(2), 564–571.

    Article  Google Scholar 

  28. Watteyne, T., Lanzisera, S., Mehta, A., & Pister, K. S. (2010). Mitigating multipath fading through channel hopping in wireless sensor networks. In 2010 IEEE international conference on communications (ICC), IEEE (pp. 1–5).

  29. Xu, G., Shen, W., & Wang, X. (2014). Applications of wireless sensor networks in marine environment monitoring: A survey. Sensors, 14(9), 16,932–16,954.

    Article  Google Scholar 

  30. Yeoh, C. M., Chai, B. L., Lim, H., Kwon, T. H., Yi, K. O., Kim, T. H., et al. (2011). Ubiquitous containerized cargo monitoring system development based on wireless sensor network technology. International Journal of Computers Communications & Control, 6(4), 779–793.

    Article  Google Scholar 

  31. Yu, X., Wu, P., Han, W., & Zhang, Z. (2013). A survey on wireless sensor network infrastructure for agriculture. Computer Standards & Interfaces, 35(1), 59–64.

    Article  Google Scholar 

  32. Yuan, S., Becker, M., Jedermann, R., Görg, C., & Lang, W. (2009). An experimental study of signal propagation and network performance in monitoring of food transportation. In 6th Annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks workshops, 2009. SECON Workshops’ 09 (pp. 1–3). IEEE.

  33. Zhao, J., & Govindan, R. (2003). Understanding packet delivery performance in dense wireless sensor networks. In Proceedings of the 1st international conference on embedded networked sensor systems (pp. 1–13). ACM.

  34. Zinonos, Z., Vassiliou, V., & Christofides, T. (2012). Radio propagation in industrial wireless sensor network environments: From testbed to simulation evaluation. In Proceedings of the 7th ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks (pp. 125–132). ACM.

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Acknowledgements

The authors would like to thank Conor Mowlds, Vivian Gough, Paul Nash and Tim P. Forde from the National Maritime College of Ireland (NMCI), as well as Commodore Hugh Tully, Lieutenant Commander David Memery and Lieutenant (NS) Padraig Reaney from the Irish Naval Service (INS), for their valuable help and support during the data collection for this paper and the overall project.

Funding

This material is based upon works supported by the Science Foundation Ireland under Grant No. 12/RC/2302, the Marine Renewable Energy Ireland (MaREI) Centre research programme.

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  1. Nimbus Centre, Cork Institute of Technology, Bishopstown, Cork, Ireland

    David Rojas & John Barrett

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  1. David Rojas
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Correspondence to David Rojas.

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Rojas, D., Barrett, J. Link quality evaluation of a wireless sensor network in metal marine environments. Wireless Netw 25, 1253–1271 (2019). https://doi.org/10.1007/s11276-018-1726-z

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