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Sensor deployment in wireless sensor networks with linear topology using virtual node concept

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Abstract

In a multi-hop wireless sensor network with a convergecast communication model, there is a high traffic accumulation in the neighborhood of the sink. This area constitutes the bottleneck of the network since the sensors deployed withing it rapidly exhaust their batteries. In this paper, we consider the problem of sensors deployment for lifetime maximization in a linear wireless sensor network. Existing approaches express the deployment recommendations in terms of distance between consecutive sensors. Solutions imposing such constraints on the deployment may be costly and difficult to manage. In this paper, we propose a new approach where the network is formed of virtual nodes, each associated to a certain geographical area. An analytical model of the network traffic per virtual node is proposed and a greedy algorithm to calculate the number of sensors that should form each virtual node is presented. Performance evaluation shows that the greedy deployment can improve the network lifetime by up to 40%, when compared to the uniform deployment. Moreover, the proposed approach outperforms the related work when complemented by a scheduling algorithm which reduces the messages overhearing. It is also shown that the lifetime of the network can be significantly improved if the battery capacity of each sensor is dimensioned taking into account the traffic it generates or relays.

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References

  1. Jawhar, I., Mohamed, N., & Agrawal, D. P. (2011). Linear wireless sensor networks: Classification and applications. Journal of Network and Computer Applications, 34(5), 1671–1682.

    Article  Google Scholar 

  2. Stajano, F., Hoult, N., Wassell, I., Bennett, P., Middleton, C., & Soga, K. (2010). Smart bridges, smart tunnels: Transforming wireless sensor networks from research prototypes into robust engineering infrastructure. Ad Hoc Networks, 8(8), 872–888.

    Article  Google Scholar 

  3. Fisher, W., Camp, T., & Krzhizhanovskaya, V. (2016). Crack detection in earth dam and levee passive seismic data using support vector machines. In Proceedings of ICCS, San Diego, CA, USA.

  4. Komguem, R. D., Stanica, R., Tchuente, M., & Valois, F. (2014). WARIM: wireless sensor networks architecture for a reliable intersection monitoring. In Proceedings of IEEE ITSC 2014, Quingdao, China.

  5. Sun, Z., Wang, P., Vuran, M., Al-Rodhaan, M., Al-Dhelaan, A., & Akyildiz, I. (2011). BorderSense: Border patrol through advances wireless sensor networks. Ad Hoc Networks, 9(3), 468–477.

    Article  Google Scholar 

  6. Perillo, M., Cheng, Z., & Heinzelman, W. (2004). On the problem of unbalanced load distribution in wireless sensor networks. In IEEE global telecommunications conference workshops, Dallas, USA (pp. 74–79).

  7. Noori, M., & Ardakani, M. (2008). Characterizing the traffic distribution in linear wireless sensor networks. IEEE Communications Letters, 12(8), 554–556.

    Article  Google Scholar 

  8. Guo, Y., Kong, F., Zhu, D., Tosun, A. Ş., & Deng, Q. (2010). Sensor placement for lifetime maximization in monitoring oil pipelines. In Proceedings of the 1st ACM/IEEE international conference on cyber-physical systems (pp. 61–68).

  9. Olariu, S., & Stojmenovic, I. (2006). Design guidelines for maximizing lifetime and avoiding energy holes in sensor networks with uniform distribution and uniform reporting. INFOCOM, 2006, 1–12.

    Google Scholar 

  10. Ok, C., Thadakamalla, H., Raghavan, U., Kumara, S., Kim, S. G., Zhang, X., & Bukkapatnam, S. (2007). Optimal transmission power in self-sustainable sensor networks for pipeline monitoring. In IEEE international conference on automation science and engineering (CASE) (pp. 591–596).

  11. Liu, X., & Mohapatra, P. (2007). On the deployment of wireless data back-haul networks. IEEE Transactions on Wireless Communications, 6(4), 1426–1435.

    Article  Google Scholar 

  12. Aberer, K., Hauswirth, M., & Salehi, A. (2006). A middleware for fast and flexible sensor network deployment. In Proceedings of the 32nd international conference on Very large data bases.

  13. Raveendranathan, N., Galzarano, S., Loseu, V., Gravina, R., Giannantonio, R., Sgroi, M., et al. (2012). From modeling to implementation of virtual sensors in body sensor networks. IEEE Sensors Journal, 12(3), 583–593.

    Article  Google Scholar 

  14. Madria, S., Kumar, V., & Dalvi, R. (2014). Sensor cloud: A cloud of virtual sensors. In IEEE Software (Vol. 31, No. 2, pp. 70–77).

  15. Rappaport, T. S. (1996). Wireless communications: Principles and practise. Upper Saddle River: Prentice Hall.

    Google Scholar 

  16. Yetgin, H., Cheung, K. T. K., El-Hajjar, M., & Hanzo, L. H. (2017). A survey of network lifetime maximization techniques in wireless sensor networks. IEEE Communications Surveys & Tutorials, 19(2), 828–854.

    Article  Google Scholar 

  17. Vicaire, P., He, T., Cao, Q., Yan, T., Zhou, G., Gu, L., et al. (2009). Achieving long-term surveillance in vigilnet. ACM Transaction Sensor Networks, 5(1), 1–39.

    Article  Google Scholar 

  18. Sevgi, C., & Koçyiğit, A. (2014). Optimal deployment in randomly deployed heterogeneous WSNs: A connected coverage approach. Journal of Network and Computer Applications, 46, 182–197.

    Article  Google Scholar 

  19. Bhuiyan, M. Z. A., Wang, G., Cao, J., & Wu, J. (2015). Deploying wireless sensor networks with fault-tolerance for structural health monitoring. IEEE Transactions on Computers, 64(2), 382–395.

    Article  MathSciNet  Google Scholar 

  20. Parrado-Garcia, F. J., Vales-Alonso, J., & Alcaraz, J. J. (2017). Optimal planning of WSN deployments for in situ lunar surveys. IEEE Transactions on Aerospace and Electronic Systems, 53(4), 1866–1879.

    Article  Google Scholar 

  21. Boubrima, A., Bechkit, W., & Rivano, H. (2017). Optimal WSN deployment models for air pollution monitoring. IEEE Transactions on Wireless Communications, 16(5), 2723–2735.

    Article  Google Scholar 

  22. Kulkarni, N., Prasad, N. R., & Prasa, R. (2018). A novel sensor node deployment using low discrepancy sequences for WSN. Wireless Personal Communications, 100(2), 241–254.

    Article  Google Scholar 

  23. Potthuri, S., Shankar, T., & Rajesh, A. (2018). Lifetime improvement in wireless sensor networks using hybrid differential evolution and simulated annealing (DESA). Ain Shams Engineering Journal, 9(4), 655–663.

    Article  Google Scholar 

  24. Domga, K.R., Stanica, R., Tchuente, M., & Valois, F. (2017). Nodes ranking in wireless sensor network with linear topology. In IEEE WD’2017, Porto, Portugal.

  25. Zahid, A. M., Kamalrulnizam, A. B., Muhammad, A., & Hafiz, M. (2018). An overview of routing techniques for road and pipeline monitoring in linear sensor networks. Wireless Networks, 24(6), 2133–2143.

    Article  Google Scholar 

  26. Plancoulaine, S., Bachir, A., & Barthel, D. (2006). WSN node energy dissipation. Technical report, France Telecom R&D, Internal Report.

  27. Ye, W., Heidemann, J., & Estrin, D. (2004). Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/ACM Transactions on Networking, 12(3), 493–506.

    Article  Google Scholar 

  28. Zhao, Y., Wu, J., Li, F., & Lu, S. (2012). On maximizing the lifetime of wireless sensor networks using virtual backbone scheduling. IEEE Transactions on Parallel and Distributed Systems, 23(8), 1528–1535.

    Article  Google Scholar 

  29. Chen, Y., Zhao, Q., Krishnamurthy, V., & Djonin, D. (2007). Transmission scheduling for optimizing sensor network lifetime: A stochastic shortest path approach. IEEE Transactions on Signal Processing, 55(5), 2294–2309.

    Article  MathSciNet  Google Scholar 

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Acknowledgements

Funding was provided by Agence Universitaire de la Francophonie, Institut National des Sciences Appliquées de Lyon and Universite de Yaounde I.

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Correspondence to Rodrigue K. Domga.

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Domga, R.K., Stanica, R., Tchuente, M. et al. Sensor deployment in wireless sensor networks with linear topology using virtual node concept. Wireless Netw 25, 4947–4962 (2019). https://doi.org/10.1007/s11276-019-02071-x

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