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An Energy-Efficient Data Reporting Scheme Based on Spectrum Sensing in Wireless Sensor Networks

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Abstract

Wireless sensor networks (WSNs) are widely used in a variety of fields including environmental and industrial monitoring. However, the battery-powered sensor devices in WSNs can suffer from a lack of energy resources problem because of their limited battery capacity. Although the energy harvesting (EH) sensor devices recently have become an attractive alternative to address the limited battery capacity problem, a small number of EH sensor devices can be deployed because of their high cost. To address this problem, we propose an energy-efficient data reporting scheme based on spectrum sensing. In the proposed scheme, each sensor device senses the spectrum over the air and then determines the transmission time of the access signal and the number of repetitions of access signal transmission. Also, the sink node resolves the collisions by detecting the variation of the received signal power. The simulation results show that the proposed scheme increases the total energy efficiency of the sensor devices and moreover it decreases the access failure probability of the sensor devices.

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References

  1. Duche, R. N., & Sarwade, N. P. (2014). Sensor node failure detection based on reound trip delay and paths in WSNs. IEEE Sensors Journal, 14(2), 455–463.

    Article  Google Scholar 

  2. Sha, K., Gehlot, J., & Greve, R. (2013). Multipath routing techniques in wireless sensor network: A servey. Springer Wireless Personal Communications, 70(2), 807–829.

    Article  Google Scholar 

  3. Chen, Y., & Zhao, Q. (2005). On the lifetime of wireless sensor networks. IEEE Communications Letters, 9(11), 976–978.

    Article  Google Scholar 

  4. Choe, H. J., Ghosh, P., & Das, S. K. (2010). QoS-aware data reporting control in cluster-based wireless sensor networks. Elsevier Computer Communications, 33(11), 1244–1254.

    Article  Google Scholar 

  5. Hwang, T., Nam, Y., So, J., Na, M., & Choi, C. (2016). Sensing-based adaptive data reporting scheme in wireless sensor networks. In Proceedings of international conference on ubiquitous and future networks (ICUFN).

  6. Zonouz, A. E., Xing, L., Vokkarane, V. M., & Sun, Y. (2016). Hybrid wireless sensor networks: A reliability, cost and energy-aware approach. IET Wireless Sensor Systems, 6(2), 42–48.

    Article  Google Scholar 

  7. Park, J., Lee, J., Hur, J., & Kang. K. (2012). Extending service corverage using FGS-aware blind repetition. In Proceedings of international conference on network-based information systems (NBiS).

  8. Ye, Y., Liu, X., & Cho. H. (2008). An energy-efficient single-hop wireless sensor network using repeat-accumulate codes. In Proceedings of international conference on communications, circuits and systems (ICCCAS).

  9. Zhai, C., Liu, J., & Zheng, L. (2016). Cooperative spectrum sharing with wireless energy harvesting in cognitive radio networks. IEEE Transactions on Vehicular Technology, 65(7), 5303–5316.

    Article  Google Scholar 

  10. Assaf, A. E., Zaidi, S., Affes, S., & Kandil, N. (2016). Low-cost localization for multihop heterogeneous wireless sensor networks. IEEE Transactions on Wireless Communications, 15(1), 472–484.

    Article  Google Scholar 

  11. Li, H., Huang, C., Zhang, P., Cui, S., & Zhang, J. (2016). Distributed opportunistic scheduling for energy harvesting based wireless networks: A two-stage probing approach. IEEE/ACM Transactions on Networking, 24(3), 1618–1631.

    Article  Google Scholar 

  12. Heinzelman, W. R., Chandrakasan, A., & Balakrishnan. H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of IEEE hawaii international conference on system science (HICSS).

  13. Rajendran, V., Obraczka, K., & Garcia-Luna-Aceves, J. J. (2006). Energy-efficient, collision-free medium access control for wireless sensor networks. Springer Wireless Networks, 12(1), 63–78.

    Article  Google Scholar 

  14. Choe, H. J., Ghosh, P., Basu, K., & Das, S. K. (2009). Class-based data reporting scheme in heterogeneous wireless sensor networks. In Proceedings of international computer communications and networks (ICCCN).

  15. Kafi, M. A., Djenouri, D., Othman, J. B., & Badache, N. (2014). Congestion control protocols in wireless snesor networks: A survey. IEEE Communications Survey & Tutorials, 16(3), 1369–1389.

    Article  Google Scholar 

  16. Mansourkiaie, F., & Ahmed, M. H. (2015). Joint cooperative routing and power allocation for collision minimization in wireless sensor networks with multiple flows. IEEE Wireless Cummunications Letters, 4(1), 6–9.

    Article  Google Scholar 

  17. Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient MAC protocol for wireless sensor networks. In Proceedings of IEEE international conference on computer communications (INFOCOM).

  18. Dam, T. V., & Langendoen, K. (2003). An adaptive energy-efficient MAC protocol for wireless sensor networks. In Proceedings of international embedded networked sensor systems (Sensys).

  19. Sun, Y., Du, S., Gurewitz, O., & Johnson, D. B. (2008). DW-MAC: A low latency, energy efficient demand-wakeup MAC protocol for wireless sensor networks. In Proceedings of ACM international symposium on mobile ad hoc networking and computing (MobiHoc).

  20. Sun, Y., Gurewitz, O., Du, S., Tang, L., & Johnson, D. B. (2003). ADB: An efficient multihop broadcast protocol based on asynchronous duty-cycling in wireless sensor networks. In Proceedings of international embedded networked sensor systems (Sensys).

  21. Bardyn, J.-P., Melly, T., Seller, O., & Sornin, N. (2016). IoT: The era of LPWAN is starting now. In Proceedings of IEEE european solied-state circuit conference (ESSCIRC).

  22. Yücek, T., & Arslan, H. (2009). A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Communications Surveys & Tutorials, 11(1), 116130.

    Article  Google Scholar 

  23. Bouabdallah, F., Bouabdallah, N., & Boutaba, R. (2009). On balancing energy consumption in wireless sensor networks. IEEE Transactions on Vehicular Technology, 58(6), 2009–2924.

    Article  MATH  Google Scholar 

  24. 3GPP TSG-RAN, (2016). Presentation of specification/report to TSG (Release 13), 3GPP TR 36.802 V1.0.0.

  25. Arnbak, J., & Blitterswijk, W. V. (1987). Capacity of slotted ALOHA in rayleigh-fading channels. IEEE Journal on Selected Areas in Communications, 5(2), 261–269.

    Article  Google Scholar 

  26. Jeon, W. S., & Jeong, D. G. (2015). Combinied channel access and sensing in cognitive radio slotted-ALOHA networks. IEEE Transactions on Vehicular Technology, 64(5), 2128–2133.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Electronic Engineering, Sogang University, Seoul, 04107, Republic of Korea

    Taemin Hwang, Yujin Nam & Jaewoo So

  2. Corporate R&D Center, SK Telecom, Seongnam, 13595, Republic of Korea

    Minsoo Na & Changsoon Choi

Authors
  1. Taemin Hwang
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  2. Yujin Nam
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  3. Jaewoo So
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  4. Minsoo Na
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  5. Changsoon Choi
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Corresponding author

Correspondence to Jaewoo So.

Additional information

This paper was presented in part at the International Conference on Ubiquitous and Future Networks (ICUFN), July 5–8, 2016 [5]. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2016R1D1A1B03934150).

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Hwang, T., Nam, Y., So, J. et al. An Energy-Efficient Data Reporting Scheme Based on Spectrum Sensing in Wireless Sensor Networks. Wireless Pers Commun 93, 949–967 (2017). https://doi.org/10.1007/s11277-017-3962-4

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  • DOI: https://doi.org/10.1007/s11277-017-3962-4

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