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Energy conscious deterministic self-healing new generation wireless sensor network: smart WSN using the Aatral framework

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Abstract

It is expected that in the next year, over a billion wireless sensor network (WSN) nodes will be deployed throughout the world, constituting a wide variety of sensor applications. In such a domain, management of the randomly distributed sensor networks is complicated by issues such as knowledge of energy consumption and coverage, extended lifetimes and demands for improved quality of service parameters. Several researchers have addressed these issues through their own innovations and discoveries of different schemes, methods, techniques or mathematical models and architectures or applications, using a variety of node designs. This in turn, has lead to multiple different choices of hardware and software options. However, this has not simplified the process of setting up application testbeds considering energy consumption. There is no readily available solution for setting up a WSN with user selected profiles and parameters. Multiple communication protocols, routing protocols, signal calibration and propagation methods, data aggregation schemes, clustering formations with multiple variations have been proposed for different research objectives. This paper proposes a method for consolidating all the initiatives and integrating these in a service panel framework that helps manage the desired WSN with options to set up an individual WSN profile and supporting the energy engineering processes involved in the WSN.

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References

  1. Satish, G. N., & Varma, P. S. (2013). Energy management system in ad hoc wireless networks. International Journal of P2P Network Trends and Technology (IJPTT), 3(3), 123–125.

    Google Scholar 

  2. Liang, Y., & Peng, W. (2010). Minimizing energy consumptions in wireless sensor networks via two-modal transmission. ACM SIGCOMM Computer Communication Review, 40(1), 12–18.

    Article  Google Scholar 

  3. Buratti, C., Conti, A., Dardari, D., & Verdone, R. (2009). An overview on wireless sensor networks technology and evolution. Sensors, 9(9), 6869–6896. doi:10.3390/s90906869.

    Article  Google Scholar 

  4. Hsieh, C.-H., Samie, F., & Srouji, M. S. (2014). Hardware/software codesign and system synthesis (CODES + ISSS). In The Proceedings of the 2014 International Conference on Hardware/Software Codesign and System Synthesis.

  5. Grindvoll, H., Vermesan, O., & Crosbie, T. (2012). A wireless sensor network for intelligent building energy management based on multi communication standards—A case study. Journal of Information Technology in Construction, 17, 43.

    Google Scholar 

  6. Yan, R., & Nanjing, Y. Q. (2012). Energy-aware sensor node design with its application in wireless sensor networks. IEEE Transactions on Instrumentation and Measurement, 62(5), 1183–1191.

    Article  Google Scholar 

  7. Rao, A. S., Gubbi, J., Ngo, T., Nguyen, J., & Palaniswami, M. (2011). Energy efficient time synchronization in WSN for critical infrastructure monitoring. In NeCoM/WeST/Simon 2011, CCIS (Vol. 197, pp. 314–323).

  8. Yao, Y., & Giannakis, G. B. (2005). Energy-efficient scheduling for wireless sensor networks. IEEE Transactions on Communications, 53(8), 1333–1342.

    Article  Google Scholar 

  9. Alippi, C., Anastasi, G., Di Francesco, M., & Roveri, M. (2009). Energy management in wireless sensor networks with energy-hungry sensors. IEEE Instrumentation and Measurement Magazine, 12(2), 16–23.

    Article  Google Scholar 

  10. Schmidt, D., Kramer, M., Kuhn, T., & Wehn, N. (2007). Energy modelling in sensor networks. Advances in Radio Science, 5, 347–351.

    Article  Google Scholar 

  11. Zhang, T., & Li, S. (2014). Design of wireless sensor network node based on CyFi technology and ARM7 system. Journal of Chemical and Pharmaceutical Research, 6, 512–519.

    Google Scholar 

  12. Narayanaswamy, K. V. (2013). Monitoring and configuration of energy harvesting system using WSN. International Journal of Scientific Research in Knowledge (IJSRK), 1(7), 212–221.

    Article  Google Scholar 

  13. Sendra, S., Lloret, J., García, M. & Toledo, J. F. (2011). Power saving and energy optimization techniques for wireless sensor networks. Journal of Communications, 6(6), 439–459.

    Google Scholar 

  14. Zhang, X., Fang, J., Meng, F., & Wei, X. (2014). A self-powered WSN based on energy harvesting of mechanical vibration. Mathematical Problems in Engineering, 2015, 1–8.

    Google Scholar 

  15. Gungor, V. C., & Hancke, G. P. (2009). Industrial wireless sensor networks: challenges, design principles, and technical approaches. IEEE Transactions on Industrial Electronics, 56(10), 4258–4265.

    Article  Google Scholar 

  16. Jiang, D., Xu, Z., Liu, J., & Zhao, W. (2015). An optimization-based robust routing algorithm to energy-efficient networks for cloud computing. Telecommunication Systems. 1–0.

  17. Jiang, D., Xu, Z., Li, W., & Chen, Z. (2014). Topology control-based collaborative multicast routing algorithm with minimum energy consumption. International Journal of Communication Systems. doi:10.1002/dac.2905.

    Google Scholar 

  18. Xu, Z., Qin, W., Tang, Q. Y., & Jiang, D. (2014). Energy-efficient cognitive access approach to convergence communications. Science China Information Sciences, 57(4), 1–12.

    Article  Google Scholar 

  19. Gowrishankar, S., Basavaraju, T. G., Manjaiah, D. H., & Sarkar, S. K. (2008). Issues in wireless sensor networks. In Proceedings of the World Congress on Engineering (WCE), I.

  20. Incebacaka, D., Bicakcib, K., & Tavlib, B. (2015). Evaluating energy cost of route diversity for security in wireless sensor networks. Computer Standards & Interfaces, 39, 44–57.

    Article  Google Scholar 

  21. Cotuk, H., Bicakci, K., Tavli, B., & Uzun, E. (2013). The impact of transmission power control strategies on lifetime of wireless sensor networks. IEEE Transactions on Computers, 99, 1.

    Google Scholar 

  22. Ramaswamy, L., Lawson, V., & Gogineni, S. (2013). Towards a quality-centric big data architecture for federated sensor service. In IEEE proceedings of the International Congress on Big Data (BigData Congress).

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Acknowledgments

We would like to thank the Vee Eee Technologies team for helping us to set up the testbeds. We also wish to express our heartfelt gratitude to the head of our department, Dr. Arumugam Sir, for his support and insightful corrections of our work. We want to acknowledge the anonymous reviewers from Springer who provided valuable feedback to improve our paper.

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Correspondence to Subramanian Anuradha.

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Thangaraj, M., Anuradha, S. Energy conscious deterministic self-healing new generation wireless sensor network: smart WSN using the Aatral framework. Wireless Netw 23, 1267–1284 (2017). https://doi.org/10.1007/s11276-016-1214-2

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