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A Fuzzy-Based Approach for Transmission Control of Sensory Data in Resilient Wireless Sensor Networks During Disaster Situation

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 159))

Abstract

Wireless sensor networks can be used for long-term operation and they can collect data effectively from huge volumes of sensed data. There are many applications of wireless sensor networks. In this paper, we propose a fuzzy-based transmission control system of sensed data for resilient wireless sensor networks in disaster situations. From the evaluation results, we found that our proposed system can reduce the transmission interval and extend the lifetime of network for disaster situations.

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References

  1. Aazam, M., Huh, E.N.: Fog computing and smart gateway based communication for cloud of things. In: Proceedings of the International Conference on Future Internet of Things and Cloud (FiCloud-2014), pp. 464–470, August 2014

    Google Scholar 

  2. Akyildiz, I.F., Kasimoglu, I.H.: Wireless sensor and actor networks: research challenges. Ad Hoc Netw. J. (Elsevier) 2(4), 351–367 (2004)

    Article  Google Scholar 

  3. Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., Ayyash, M.: Internet of Things: a survey on enabling technologies, protocols, and applications. IEEE Commun. Surv. Tutorials 17(4), 2347–2376 (2015)

    Article  Google Scholar 

  4. Akan, Ö.B., Akyildiz, I.F.: Event-to-sink reliable transport in wireless sensor networks. IEEE/ACM Trans. Netw. 13(5), 1003–1016 (2005)

    Article  Google Scholar 

  5. Balan, K., Manuel, M.P., Faied, M., Krishnan, M., Santora, M.: A fuzzy based accessibility model for disaster environment. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-2019), pp. 2304–2310, May 2019

    Google Scholar 

  6. Forlizzi, J., DiSalvo, C.: Service robots in the domestic environment: a study of the roomba vacuum in the home. In: Proceedings of the 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction (ACM HRI-2006), Utah, US, pp. 258–265, March 2006

    Google Scholar 

  7. Guo, Z., Li, G., Zhou, M., Feng, W.: Resilient configuration approach of integrated community energy system considering integrated demand response under uncertainty. IEEE Access 7, 87513–87533 (2019)

    Article  Google Scholar 

  8. Gupta, I., Riordan, D., Sampalli, S.: Cluster-head election using fuzzy logic for wireless sensor networks. In: Proceedings of the 3rd Annual Communication Networks and Services Research Conference (CNSR-2005), pp. 255–260 (2005)

    Google Scholar 

  9. Jiang, X., Dawson-Haggerty, S., Dutta, P., Culler, D.: Design and implementation of a high-fidelity ac metering network. In: Proceedings of the International Conference on Information Processing in Sensor Networks 2009 (IPSN-2009), San Francisco, US, pp. 253–264, April 2009

    Google Scholar 

  10. Li, T.S., Chang, S.J., Tong, W.: Fuzzy target tracking control of autonomous mobile robots by using infrared sensors. IEEE Trans. Fuzzy Syst. 12(4), 491–501 (2004)

    Article  Google Scholar 

  11. Mendel, J.M.: Fuzzy logic systems for engineering: a tutorial. Proc. IEEE 83(3), 345–377 (1995)

    Article  Google Scholar 

  12. Petrakis, E.G.M., Sotiriadis, S., Soultanopoulos, T., Renta, P.T., Buyya, R., Bessis, N.: Internet of things as a service (iTaaS): challenges and solutions for management of sensor data on the cloud and the fog. Internet Things 3–4, 156–174 (2018)

    Article  Google Scholar 

  13. Reddy, G.H., Chakrapani, P., Goswami, A.K., Choudhury, N.B.D.: Fuzzy based approach for restoration of distribution system during post natural disasters. IEEE Access 6, 3448–3458 (2018)

    Article  Google Scholar 

  14. Ruan, J., Jiang, H., Li, X., Shi, Y., Chan, F.T.S., Rao, W.: A granular GA-SVM predictor for big data in agricultural cyber-physical systems. IEEE Trans. Ind. Inf. 15(12), 6510–6521 (2019)

    Article  Google Scholar 

  15. Schmitt, S., Will, H., Aschenbrenner, B., Hillebrandt, T., Kyas, M.: A reference system for indoor localization testbeds. In: Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN-2012), Sydney, Australia, pp. 1–8, November 2012

    Google Scholar 

  16. Sengupta, S., Das, S., Nasir, M., Vasilakos, A.V., Pedrycz, W.: An evolutionary multiobjective sleep-scheduling scheme for differentiated coverage in wireless sensor networks. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 42(6), 1093–1102 (2012)

    Google Scholar 

  17. Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., Hubert, T., Baker, L., Lai, M., Bolton, A., Chen, Y., Lillicrap, T., Hui, F., Sifre, L., van den Driessche, G., Graepel, T., Hassabis, D.: Mastering the game of Go without human knowledge. Nature 550, 354–359 (2017)

    Article  Google Scholar 

  18. Su, X., Wu, L., Shi, P.: Sensor networks with random link failures: distributed filtering for T-S fuzzy systems. IEEE Trans. Ind. Inf. 9(3), 1739–1750 (2013)

    Article  Google Scholar 

  19. Sung, J.Y., Guo, L., Grinter, R.E., Christensen, H.I.: My Roomba is Rambo: intimate home appliances. In: Proceedings of the 9th International Conference on Ubiquitous Computing (UbiComp-2007), Seoul, South Korea, pp. 145–162, September 2007

    Google Scholar 

  20. Tribelhorn, B., Dodds, Z.: Evaluating the roomba: a low-cost, ubiquitous platform for robotics research and education. In: Proceedings of the IEEE International Conference on Robotics and Automation (IEEE ICRA-2007), Roma, Italy, pp. 1393–1399, April 2007

    Google Scholar 

  21. Tsuchiya, G., Ikeda, M., Elmazi, D., Barolli, L., Kulla, E.: A disaster information gathering system design using fuzzy logic. In: Proceedings of The 12th International Conference on Broad-Band Wireless Computing, Communication and Applications (BWCCA-2017), pp. 854–861, Nov 2017

    Google Scholar 

  22. Xia, J., Yun, R., Yu, K., Yin, F., Wang, H., Bu, Z.: A coordinated mechanism for multimode user equipment accessing wireless sensor network. Int. J. Grid Util. Comput. 5(1), 1–10 (2014)

    Article  Google Scholar 

  23. Yu, Y., Rittle, L.J., Bhandari, V., LeBrun, J.B.: Supporting concurrent applications in wireless sensor networks. In: Proceedings of the 4th ACM International Conference on Embedded Networked Sensor Systems (ACM SenSys-2006), Boulder, US, pp. 139–152, November 2006

    Google Scholar 

  24. Yuriyama, M., Kushida, T.: Integrated cloud computing environment with IT resources and sensor devices. Int. J. Space-Based Situated Comput. 1(2/3), 163–173 (2011)

    Article  Google Scholar 

  25. Zadeh, L.: Fuzzy logic, neural networks, and soft computing. ACM Commun. 77–84 (1994)

    Google Scholar 

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Acknowledgments

This work has been partially funded by the research project from Comprehensive Research Organization at Fukuoka Institute of Technology (FIT), Japan.

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Correspondence to Makoto Ikeda .

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Nishii, D., Ikeda, M., Barolli, L. (2021). A Fuzzy-Based Approach for Transmission Control of Sensory Data in Resilient Wireless Sensor Networks During Disaster Situation. In: Barolli, L., Takizawa, M., Enokido, T., Chen, HC., Matsuo, K. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2020. Lecture Notes in Networks and Systems, vol 159. Springer, Cham. https://doi.org/10.1007/978-3-030-61108-8_29

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  • DOI: https://doi.org/10.1007/978-3-030-61108-8_29

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  • Print ISBN: 978-3-030-61107-1

  • Online ISBN: 978-3-030-61108-8

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