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Mobile sink discovery mechanism in wireless sensor networks with duty cycles

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Abstract

Wireless sensor network (WSN) is a multi-hop, self-organizing distributed network system composed of multiple micro-sensors through wireless communication. There are problems such as energy holes and transmission link interruption due to node failure for multi-hop mode of data transmission. Mobile sink (MS) supports data forwarding and collection to avoid multi-hop transmission, extending network life by saving network energy. In the work, we discussed transmission energy and delay problems of data collection by MS in WSN with duty cycle. Based on fixed MS moving speed and regular transmission performance, the network life cycle was maximized to propose an asynchronous path independent energy efficient algorithm irrelevant to the path. After that, the efficiency of the protocol was verified by experiments.

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References

  1. Akyildiz, I F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A survey on sensor networks. IEEE Commun. Mag. 40(8), 102–114 (2002)

    Article  Google Scholar 

  2. Ren, F.Y., Huang, H.N., Lin, C.: Wireless sensor networks. J. Softw. 14(7), 1282–1291 (2003)

    MATH  Google Scholar 

  3. Li, M., He, Y., Liu, Y., Zhao, J., Tang, S., Li, X., Dai, G.: Canopy closure estimates with greenorbs: sustainable sensing in the forest[C]. In: Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (Sensys), pp. 99–112 (2009)

  4. Luo, J., Zhang, Q., Wang, D.: Delay tolerant event collection for underground coal mine using mobile sinks. In: Proceedings of the IEEE International Workshop on Quality of Service (IWQoS), pp. 1–9 (2009)

  5. Xing, G., Wang, T., Xie, Z., Jia, W.: Rendezvous planning in wireless sensor networks with mobile elements. IEEE Trans. Mob. Comput. 7(12), 1430–1443 (2008)

    Article  Google Scholar 

  6. Gao, S., Zhang, H.K.: Optimal path selection for mobile sink in delay-guaranteed sensor networks. Acta Electron. Sin. 39(4), 742–747 (2011)

    Google Scholar 

  7. Dantu, K., Rahimi, M., Shah, H., Babel, S., Dhariwal, A., Sukhatme, GS.: Robomote: enabling mobility in sensor networks. In: Proceedings of the ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), pp. 404–409 (2005)

  8. Gao, S., Zhang, H., Das, S.K.: Efficient data collection in wireless sensor networks with path-constrained mobile sinks. Mob. Comput. 4, 592–608 (2011)

    Google Scholar 

  9. Erman, A.T., Dilo, A., Havinga, P.: A fault-tolerant data dissemination based on honeycomb architecture for mobile multi-sink wireless sensor networks. In: International Conference on Intelligent Sensors, pp. 97–102 (2017)

  10. Hawbani, A., Wang, X., Kuhlani, H., Karmoshi, S., Ghoul, R.: Sink-oriented tree based data dissemination protocol for mobile sinks wireless sensor networks. Wirel. Netw. 2, 1–12 (2017)

    Google Scholar 

  11. Xia, R., Tian, Y.-C., Li, Y., Sung, Y.: Wireless sensor/actuator network design for mobile control applications. Sensors 7(7), 2157–2173 (2007)

    Article  Google Scholar 

  12. Wang, Y., Wu, H.Y., Dang, H., Lin, F.: Analytic, simulation, and empirical evaluation of delay/fault-tolerant mobile sensor networks. IEEE Trans. Wirel. Commun. 1(11), 3287–3296 (2007)

    Google Scholar 

  13. Luo, J., Zhang, Q., Wang, D.: Delay tolerant event collection for underground coal mine using mobile sinks. In: Proceedings of the IEEE International Workshop on Quality of Service (IWQoS), pp. 1–9 (2009)

  14. Chebrolu, K., Raman, B., Mishra, N., Valiveti, PK., Kumar, R.: BriMon: A sensor network system for railway bridge monitoring. In: Proceedings of the ACM International Conference on Mobile Systems, Applications, and Services (Mobisys), pp. 2–14 (2008)

  15. Ammari, H., Das, S.: Data dissemination to mobile sinks in wireless sensor networks: an information theoretic approach. In: Proceedings of the 2th IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS), pp. 305–314 (2005)

  16. Ye, W., Heidemann, J., Estrin, D.: Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/ACM Trans. Netw. 12(3), 493–506 (2004)

    Article  Google Scholar 

  17. Ye, W., Silva, F., Heidemann, J.: Ultra-low duty cycle MAC with scheduled channel polling. In: Proceedings of the 4th International Conference on Embedded Networked Sensor Systems (Sensys), pp. 321–334 (2006)

  18. Chakrabarti, A., Sabharwal, A., and Aazhang, B.: Using predictable observer mobility for power efficient design of sensor networks. In: Proceedings of the ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), pp. 129–145 (2003)

    Chapter  MATH  Google Scholar 

  19. Polastre, J., Hill, J., and Culler, D.: Versatile low power media access for sensor networks. In: Proceedings of the 2nd ACM Conference on Embedded Networked Sensor Systems (SenSys), pp. 95–107 (2004)

  20. Yang, X., Vaidya, N.: A wakeup scheme for sensor networks: Achieving balance between energy saving and end-to-end delay. In: Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), pp. 19–26 (2004)

  21. Anastasi, G., Conti, M., Francesco, M.D., Passarella, A.: Energy conservation in wireless sensor networks: a survey. Ad Hoc Netw. 7(3), 537–568 (2009)

    Article  Google Scholar 

  22. Chakrabarti, A., Sabharwal, A., and Aazhang, B.: Using predictable observer mobility for power efficient design of sensor networks. In: Proceedings of the ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), pp. 129–145 (2003)

    Chapter  MATH  Google Scholar 

  23. Yang, X., Vaidya, N.: A wakeup scheme for sensor networks: Achieving balance between energy saving and end-to-end delay. In: Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), pp. 19–26 (2004)

  24. Anastasi, G., Conti, M., Francesco, M.D.: Reliable and energy-efficient data collection in sparse sensor networks with mobile elements. Perform. Eval. 66(12), 791–810 (2009)

    Article  Google Scholar 

  25. Anastasi, G., Borgia, E., Conti, M., Gregori, E.: A hybrid adaptive protocol for reliable data delivery in WSNs with multiple mobile sinks. Comput. J. 54(2), 213–228 (2011)

    Article  Google Scholar 

  26. Anastasi, Q., Conti, M., and Francesco, M.D.: An analytical study of reliable and energy efficient data collection in sparse sensor networks with mobile elements. In: Proceedings of the European Conference on Wireless Sensor Networks (EWSN), pp. 199–215 (2009)

  27. Sugihara, R., Gupta, R.K.: Optimal speed control of mobile node for data collection in sensor networks. IEEE Trans. Mob. Comput. 9(1), 127–139 (2010)

    Article  Google Scholar 

  28. Francesco, D.M., Das, S.K., Anastasi, G.: Data collection in wireless sensor networks with mobile elements: a survey. ACM Trans. Sens. Netw. 8(1), 1805–1821 (2011)

    Article  Google Scholar 

  29. Schurgers, C., Tsiatsis, V., Ganeriwal, S., Srivastava, M.B.: Optimizing sensor networks in the energy-latency-density design space. IEEE Trans. Mob. Comput. 1(1), 70–80 (2002)

    Article  Google Scholar 

  30. Liu, R., Pan, T., Li, Z.: Multi-model recursive identification for nonlinear systems with non-uniformly sampling. Clust. Comput. 20, 25 (2017). https://doi.org/10.1007/s10586-016-0688-0

    Article  Google Scholar 

  31. Ranran, Liu, Enxing, Zheng, Shan, Chang, Shaoyi, Bei, Lanchun, Zhang: Hierarchical stochastic gradient identification for non-uniformly sampling Hammerstein systems with colored noise. Comput. Syst. Sci. Eng. 31(6), 425–430 (2016)

    Google Scholar 

  32. Mainland, G., Parkes, D., Welsh, M.: Decentralized, adaptive resource allocation for sensor networks. In: Proceedings of IEEE NSDI, pp. 315–328 (2005)

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Acknowledgements

This work was supported in part by Jiangsu Policy Guidance (Industry University Research) Project (Grant Nos. BY2016030-08 and BY2016030-16), Major horizontal project (Grant No. KYH15052), Talent Introduction Project (Grant No. KYY15016) and Jiangsu Planned Projects for Postdoctoral Research Funds (Grant No. 1601138B).

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Authors and Affiliations

  1. Information Center of Jiangsu University of Technology, Changzhou, 213001, Jiangsu, China

    Yifeng Jiang

  2. School of Automotive and Traffic Engineering, Jiangsu University of Technology, Changzhou, 213001, Jiangsu, China

    Ranran Liu

  3. School of Electrical and Information Engineering, Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou, China

    Enxing Zheng

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  1. Yifeng Jiang
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  2. Ranran Liu
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  3. Enxing Zheng
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Correspondence to Ranran Liu.

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Jiang, Y., Liu, R. & Zheng, E. Mobile sink discovery mechanism in wireless sensor networks with duty cycles. Cluster Comput 22 (Suppl 3), 5655–5662 (2019). https://doi.org/10.1007/s10586-017-1449-4

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  • DOI: https://doi.org/10.1007/s10586-017-1449-4

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