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Trading sensing coverage for an extended network lifetime

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Abstract

One of the main benefits of using Wireless Sensor Networks (WSNs) is that they can be deployed in remote locations without any prior infrastructure. Because of this nodes are normally battery powered. This limits the lifetime of the network. In this paper, we propose a novel method of scheduling nodes based on a user’s sensing coverage requirement. Through the use of our proposed scheduling algorithm (Ncut-GA), it is shown that the duration for which the user’s coverage requirement is met can be extended. When compared with a previously published algorithm (Greedy-MSC), the proposed algorithm is able to increase coverage duration by up to 80%. Furthermore it is also shown that the time until the first node dies can be improved by up to 200% through the use of Ncut-GA.

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References

  1. Bulut, E., & Korpeoglu, I. (2007). DSSP: a dynamic sleep scheduling protocol for prolonging the lifetime of wireless sensor networks. In 21st international conference on advanced information networking and applications workshops, 2007, AINAW’07 (Vol. 2).

    Google Scholar 

  2. Cardei, M., & Du, D. (2005). Improving wireless sensor network lifetime through power aware organization. Wireless Networks, 11(3), 333–340.

    Article  Google Scholar 

  3. Cardei, M., Thai, M., Li, Y., & Wu, W. (2005). Energy-efficient target coverage in wireless sensor networks. In Proceedings IEEE INFOCOM 2005, 24th annual joint conference of the IEEE computer and communications societies (Vol. 3).

    Google Scholar 

  4. Georganas, N. (2002). A coverage-preserving node scheduling scheme for large wireless sensor networks. In Proceedings of the 1st ACM international workshop on wireless sensor networks and applications (pp. 32–41). New York: ACM.

    Google Scholar 

  5. Gnawali, O., Jang, K., Paek, J., Vieira, M., Govindan, R., Greenstein, B., Joki, A., Estrin, D., & Kohler, E. (2006). The tenet architecture for tiered sensor networks. In Proceedings of the 4th international conference on Embedded networked sensor systems (pp. 153–166). New York: ACM.

    Chapter  Google Scholar 

  6. Gupta, H., Navda, V., Das, S., & Chowdhary, V. (2008). Efficient gathering of correlated data in sensor networks. ACM Transactions on Sensor Networks, 4(1), 1–31. doi:10.1145/1325651.1325655.

    Article  Google Scholar 

  7. Pazand, B., & Datta, A. (2008). An energy-efficient node-scheduling scheme for wireless sensor networks based on minimum dominating sets. International Journal of Network Management. doi:10.1002/nem.689.

  8. Raghunathan, V., Schurgers, C., Park, S., & Srivastava, M. (2002). Energy-aware wireless microsensor networks. IEEE Signal Processing Magazine, 19(2), 40–50.

    Article  Google Scholar 

  9. Shi, J., & Malik, J. (2000). Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8), 888–905.

    Article  Google Scholar 

  10. Wang, L., & Kulkarni, S. (2008). Sacrificing a little coverage can substantially increase network lifetime. Ad Hoc Networks, 6(8), 1281–1300.

    Article  Google Scholar 

  11. Wang, W., Srinivasan, V., Chua, K., & Wang, B. (2007). Energy-efficient coverage for target detection in wireless sensor networks. In Proceedings of the 6th international conference on information processing in sensor networks (pp. 313–322). New York: ACM.

    Chapter  Google Scholar 

  12. Wang, X., Xing, G., Zhang, Y., Lu, C., Pless, R., & Gill, C. (2003). Integrated coverage and connectivity configuration in wireless sensor networks. In Proceedings of the 1st international conference on Embedded networked sensor systems (pp. 28–39). New York: ACM.

    Chapter  Google Scholar 

  13. Yen, L., Yu, C., & Cheng, Y. (2006). Expected k-coverage in wireless sensor networks. Ad Hoc Networks, 4(5), 636–650.

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Complex & Adaptive Systems Laboratory, School of Computer Science and Informatics, University College Dublin, Dublin, Ireland

    Jong Chern Lim & C. J. Bleakley

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  1. Jong Chern Lim
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  2. C. J. Bleakley
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Correspondence to Jong Chern Lim.

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Lim, J.C., Bleakley, C.J. Trading sensing coverage for an extended network lifetime. Telecommun Syst 52, 2667–2675 (2013). https://doi.org/10.1007/s11235-011-9595-0

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  • DOI: https://doi.org/10.1007/s11235-011-9595-0

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