Abstract
The autonomous deployments using wireless sensor networks (WSNs) and their ability to self-organize play a vital role in data gathering in hostile environment or mission-critical applications. The contributions of this paper are threefold. First, the study in this paper proposes a preliminary model for peer-to-peer wireless power transfer (WPT) between sensor nodes, which is termed as self-energizing technique. Second, a fundamental design of a sensor node suitable for the self-energizing model is proposed, and third, using a clustering algorithm along with the flow mechanism to utilize the self-energizing technique is demonstrated. The study in this paper is a preliminary step toward proposing self-energizing technique between the peer sensor nodes of a deployed WSN. The paper concludes with the fact that the implications of self-energizing capabilities have the potential to enhance the fundamental deployment and design of such ad hoc networks.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Rai, R., Rai, P.: Survey on energy-efficient routing protocols in wireless sensor networks using game theory. In: Sarma, H., Borah, S., Dutta, N. (eds.) Advances in Communication, Cloud, and Big Data. Lecture Notes in Networks and Systems, vol. 31. Springer, Singapore (2019)
Haque, M., Ahmad, T., Imran, M.: Review of hierarchical routing protocols for wireless sensor networks. In: Hu, Y.C., Tiwari, S., Mishra, K., Trivedi, M. (eds.) Intelligent Communication and Computational Technologies. Lecture Notes in Networks and Systems, vol. 19, Springer, Singapore (2018)
Mazumdar, N., Roy, S., Nayak, S.: A survey on clustering approaches for wireless sensor networks. In: 2018 2nd International Conference on Data Science and Business Analytics IEEE (ICDSBA), Changsha, China, pp. 236–240 (2018) https://doi.org/10.1109/icdsba.2018.00049
Varghese, V., Nene, M.: Battlefield-of-Things and its implications in modern day battlefield, pp. 735–740. IEEE, ICCIC. https://doi.org/10.1109/iccic.2017.8524515 (2017)
Misra, S., Kumar, R.: A literature survey on various clustering approaches in wireless sensor network. Int. Conf. Commun. Control. Intell. Syst. IEEE 18–22
Hu, J., Luo, J., Zheng, Y., Li, K.: Graphene-grid deployment in energy harvesting cooperative wireless sensor networks for green IoT. IEEE Trans. Ind. Inform. https://doi.org/10.1109/tii.2018.2871183
Fan, Z., Jie, Z., Yujie, Q.: A multi-node rechargeable algorithm via wireless charging vehicle with optimal traveling path in wireless rechargeable sensor networks. In: 2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN), Prague, 2018, pp. 531–536. https://doi.org/10.1109/icufn.2018.8437035
Wu, T., Yang, P., Dai, H., Li, P., Rao, X.: Near optimal bounded route association for drone-enabled rechargeable WSNs. Comput. Netw. 145:107–117 (2018). ISSN 1389-1286. https://doi.org/10.1016/j.comnet.2018.07.004
Hamrioui, S., Lorenz, P., Lloret, J.: Telecommun. Syst. 67(179) (2018). Springer US https://doi.org/10.1007/s11235-017-0332-1
Eledlebi, K., Ruta, D., Saffre, F., Al-Hammadi, Y., Isakovic, A.F.: A model for self-deployment of autonomous mobile sensor network in an unknown indoor environment. In: Zhou, Y., Kunz, T. (eds.) Ad Hoc Networks. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 223 Springer, Cham (2018)
Cong, H., Li, Q., Zhou, C., Yang, Q.: Analysis on connectivity of energy harvesting wireless sensor networks based on simulation. In: 2018 International Conference on Computing, Networking and Communications (ICNC), Maui, HI, 2018, pp. 762–768. https://doi.org/10.1109/iccnc.2018.8390272
Yu, W., Choi, J., Kim, Y., Lee, W., Kim, S.: Self-organizing localization with adaptive weights for wireless sensor networks. IEEE Sens. J. 18(20), 8484–8492 (2018). https://doi.org/10.1109/jsen.2018.2866053
Seo, S., Won, J., Sultana, S., Bertino, E.: Effective key management in dynamic wireless sensor networks. IEEE Trans. Inf. Forensics Secur. 10(2), 371–383 (2015). https://doi.org/10.1109/TIFS.2014.2375555
Shehab, A., Elhoseny, M. Sahlol, A.T., Aziz, M.A.E.: Self-organizing single-hop wireless sensor network using a genetic algorithm: longer lifetimes and maximal throughputs. In: 2017 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS), Srivilliputhur, 2017, pp. 1–6. https://doi.org/10.1109/itcosp.2017.8303105
Desai, S.S., Nene, M.: DANES—Distributed Algorithm for Node Energy-Management for Self-organizing Wireless Sensor Networks, pp. 1296–1301 (2016) https://doi.org/10.1109/rteict.2016.7808041
Xie, L., et al.: Making sensor networks immortal: an energy-renewal approach with wireless power transfer. IEEE/ACM Trans. Net. 20(6), 1748–1761 (2012)
Ajmal, T., Jazani, D., Allen, B.: Design of a compact RF energy harvester for wireless sensor networks. IET Conf. Wirel. Sens. Syst. (WSS), pp. 1–5. London, UK (2012)
Griffin, B., Detweiler, C.: Resonant wireless power transfer to ground sensors from a UAV. In: 2012 IEEE International Conference on Robotics and Automation (2012). https://doi.org/10.1109/icra.2012.6225205
Wu, T., Yang, P., Dai, H., Li, P., Rao, X.: Near optimal bounded route association for drone-enabled rechargeable WSNs. Comput. Netw. 145, 107–117 (2018). ISSN 1389-1286 https://doi.org/10.1016/j.comnet.2018.07.004
Tesla, N.: The transmission of electrical energy without wires. Elect, World Engineer (1904)
Lu, X., Niyato, D., Wang, P.: Kim, D.I., Han, Z.: Wireless charger networking for mobile devices: fundamentals, standards, and applications. IEEE Wirel. Commun. 22(2), 126–135 (2015). https://doi.org/10.1109/mwc.2015.7096295
Mou, X., Sun, H.: Wireless power transfer: survey and roadmap. In: 2015 IEEE 81st Vehicular Technology Conference (VTC Spring), Glasgow, 2015, pp. 1–5. https://doi.org/10.1109/vtcspring.2015.7146165
Ho, S.L., Wang, J., Fu, W.N., Sun, M.: A comparative study between novel witricity and traditional inductive magnetic coupling in wireless charging. IEEE Trans. Magn. 47(5), 1522–1525 (2011). https://doi.org/10.1109/tmag.2010.2091495
Dai, J., Ludois, D.C.: A survey of wireless power transfer and a critical comparison of inductive and capacitive coupling for small gap applications. IEEE Trans. Power Electron. 30(11), 6017–6029 (2015). https://doi.org/10.1109/tpel.2015.2415253
Zhang, Q., Fang, W., Liu, Q., Wu, J., Xia, P., Yang, L.: Distributed laser charging: a wireless power transfer approach. IEEE Internet Things J. 5(5), 3853–3864. https://doi.org/10.1109/jiot.2018.2851070
Liu, Q., Wu, J., Xia, P., Zhao, S., Chen, W., Yang, Y., Hanzo, L.: Charging unplugged: will distributed laser charging for mobile wireless power transfer work?” IEEE Veh. Technol. Mag. 11(4), 36–45 (2016)
Nayak, P., Devulapalli, A.: A Fuzzy logic-based clustering algorithm for WSN to extend the network lifetime. IEEE Sens. J. 16(1), 137–144 (2016). https://doi.org/10.1109/jsen.2015.2472970
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Singh, A., Nene, M.J. (2020). Self-energizing Wireless Sensor Network. In: Chaudhary, A., Choudhary, C., Gupta, M., Lal, C., Badal, T. (eds) Microservices in Big Data Analytics. Springer, Singapore. https://doi.org/10.1007/978-981-15-0128-9_14
Download citation
DOI: https://doi.org/10.1007/978-981-15-0128-9_14
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-0127-2
Online ISBN: 978-981-15-0128-9
eBook Packages: Computer ScienceComputer Science (R0)