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Wireless Networks

, Volume 25, Issue 1, pp 355–365 | Cite as

Probabilistic coverage in directional sensor networks

  • Pengju SiEmail author
  • Chengdong Wu
  • Yunzhou Zhang
  • Hao Chu
  • He Teng
Article
  • 169 Downloads

Abstract

Correct and realistic sensing model is of great significance for sensor networks to perform environmental monitoring. However, the sensing capabilities of directional sensors are usually affected by environmental factors and intrinsic properties. As a result, it is not suitable to use simple binary sensing model for directional sensor networks (DSNs). In this paper, we consider probabilistic sensing models for DSNs to have practical considerations. Firstly, an exponential decay probabilistic sensing model for DSNs is considered reference to omni-directional probabilistic sensing model for traditional sensor. Secondly, we propose a fault-tolerant probabilistic sensing model with respect to orientation error and rotation error. Furthermore, combined the exponential decay probability with the fault-tolerant probability, a hybrid probabilistic sensing model is formed for DSNs. Then, based on our probability sensing models, a probabilistic coverage algorithm is introduced for random deployment to compute the coverage probability of DSNs. Performance results demonstrate that the proposed algorithm with probabilistic sensing models for DSNs is capable of providing desirable surveillance level.

Keywords

Directional sensor networks Probabilistic sensing model Coverage probability Random deployment Algorithm 

Notes

Acknowledgements

This research was supported in parts by Supported by National Natural Science Foundation of China (61471110, 61273078); Fundamental Research Funds for the Central Universities (N160413002, N160404003, N162610004); Foundation of Liaoning Provincial Department of Education (L2014090).

References

  1. 1.
    Ahmed, N., Kanhere, S., & Jha, S. (2005). Probabilistic coverage in wireless sensor networks. In Proceedings of the IEEE LCN.Google Scholar
  2. 2.
    Akyildiz, I. F., Pompili, D., & Melodia, T. (2005). Underwater acoustic sensor networks: Research challenges. Ad Hoc Networks, 3(3), 257–279.Google Scholar
  3. 3.
    Akyildiz, I. F., Melodia, T., & Chowdhury, K. R. (2007). A survey on wireless multimedia sensor networks. Computer Networks, 51(4), 921–960.Google Scholar
  4. 4.
    Al-Hourani, A., & Kandeepan, S. (2016). On modeling coverage and rate of random cellular networks under generic channel fading. Wireless Networks, 22(8), 2623–2635.Google Scholar
  5. 5.
    Assad, N., Elbhiri, B., Faqihi, M. A., Ouadou, M., & Aboutajdine, D. (2016). Efficient deployment quality analysis for intrusion detection in wireless sensor networks. Wireless Networks, 22(3), 991–1006.Google Scholar
  6. 6.
    Bhatt, R., & Datta, R. (2015). A two-tier strategy for priority based critical event surveillance with wireless multimedia sensors. Wireless Networks, 22(1), 1–18.Google Scholar
  7. 7.
    Cai, Y., Lou, W., Li, M., & Li, X. Y. (2009). Energy efficient target-oriented scheduling in directional sensor networks. IEEE Transactions on Computers, 58(9), 1259–1274.MathSciNetzbMATHGoogle Scholar
  8. 8.
    Chen, J., Li, J., & Lai, T. H. (2013). Energy-efficient intrusion detection with a barrier of probabilistic sensors: Global and local. IEEE Transactions on Wireless Communications, 12(9), 4742–4755.Google Scholar
  9. 9.
    Chen, J., Wang, B., Liu, W., Yang, L. T., & Deng, X. (2014). Rotating directional sensors to mend barrier gaps in a line-based deployed directional sensor network. IEEE Systems Journal, 99, 1–12.Google Scholar
  10. 10.
    Guvensan, M. A., & Yavuz, A. G. (2011). On coverage issues in directional sensor networks: A survey. Ad Hoc Networks, 9(7), 1238–1255.Google Scholar
  11. 11.
    Han, G., Liu, L., Jiang, J., Shu, L., & Hancke, G. (2017). Analysis of energy-efficient connected target coverage algorithms for industrial wireless sensor networks. IEEE Transactions on Industrial Informatics, 13(1), 135–143.Google Scholar
  12. 12.
    Hefeeda, M., & Ahmadi, H. (2010). Energy-efficient protocol for deterministic and probabilistic coverage in sensor networks. IEEE Transactions on Parallel and Distributed Systems, 21(5), 579–593.Google Scholar
  13. 13.
    Hong, Y., Yan, R., Zhu, Y., Li, D., & Chen, W. (2017). Finding best and worst-case coverage paths in camera sensor networks for complex regions. Ad Hoc Networks, 56, 202–213.Google Scholar
  14. 14.
    Jiang, J., Han, G., Shu, L., Chan, S., & Wang, K. (2017). A trust model based on cloud theory in underwater acoustic sensor networks. IEEE Transactions on Industrial Informatics, 13(1), 342–350.Google Scholar
  15. 15.
    Kim, D., Wang, W., Son, J., Wu, W., Lee, W., & Tokuta, A. O. (2016). Maximum lifetime combined barrier-coverage of weak static sensors and strong mobile sensors. IEEE Transactions on Mobile Computing, 16(99), 1–12.Google Scholar
  16. 16.
    Li, J., Chen, J., & Lai, T. H. (2012). Energy-efficient intrusion detection with a barrier of probabilistic sensors. In Proceedings of the IEEE INFOCOM (pp. 118–126).Google Scholar
  17. 17.
    Lin, T. Y., Santoso, H. A., Wu, K. R., & Wang, G. L. (2017). Enhanced deployment algorithms for heterogeneous directional mobile sensors in a bounded monitoring area. IEEE Transactions on Mobile Computing, 16(3), 744–758.Google Scholar
  18. 18.
    Liu, T., Lin, H., Wang, C., Peng, K., Wang, D., Deng, T., et al. (2016). Chain-based barrier coverage in WSNs: Toward identifying and repairing weak zones. Wireless Networks, 22(2), 523–536.Google Scholar
  19. 19.
    Ma, H., & Liu, Y. (2007). Some problems of directional sensor networks. International Journal of Sensor Networks, 2(1/2), 44–52.Google Scholar
  20. 20.
    Ma, H., Zhang, X., & Ming, A. (2009). A coverage-enhancing method for 3D directional sensor networks. In Proceedings of the IEEE INFOCOM.Google Scholar
  21. 21.
    Meguerdichian, S., Koushanfar, F., Potkonjak, M., & Srivastava, M. (2001). Coverage problems in wireless ad-hoc sensor networks. In Proceedings of the IEEE INFOCOM.Google Scholar
  22. 22.
    Onur, E., Ersoy, C., & Deliç, H. (2006). How many sensors for an acceptable breach detection probability? Computer Communications, 29(2), 173–182.Google Scholar
  23. 23.
    Pananjady, A., Bagaria, V. K., & Vaze, R. (2017). Optimally approximating the coverage lifetime of wireless sensor networks. IEEE/ACM Transactions on Networking, 25(1), 98–111.Google Scholar
  24. 24.
    Tao, S., Kudo, M., Pei, B. N., Nonaka, H., & Toyama, J. (2015). Multiperson locating and their soft tracking in a binary infrared sensor network. IEEE Transactions on Human–Machine Systems, 45(5), 550–561.Google Scholar
  25. 25.
    Wang, Z., Liao, J., Cao, Q., Qi, H., & Wang, Z. (2014). Achieving k-barrier coverage in hybrid directional sensor networks. IEEE Transactions on Mobile Computing, 13(7), 1443–1455.Google Scholar
  26. 26.
    Xu, B., Zhu, Y., Kim, D., Li, D., Jiang, H., & Tokuta, A. O. (2016). Strengthening barrier-coverage of static sensor network with mobile sensor nodes. Wireless Networks, 22(1), 1–10.Google Scholar
  27. 27.
    Yang, Q., He, S., Li, J., Chen, J., & Sun, Y. (2015). Energy-efficient probabilistic area coverage in wireless sensor networks. IEEE Transactions on Vehicular Technology, 64(1), 367–377.Google Scholar
  28. 28.
    Yildiz, E., Akkaya, K., Sisikoglu, E., & Sir, M. Y. (2014). Optimal camera placement for providing angular coverage in wireless video sensor networks. IEEE Transactions on Computers, 63(7), 1812–1825.MathSciNetzbMATHGoogle Scholar
  29. 29.
    Yu, Z., Yang, F., Teng, J., Champion, A., & Xuan, D. (2015). Local face-view barrier coverage in camera sensor networks. In: Proceedings of the IEEE INFOCOM.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Pengju Si
    • 1
    Email author
  • Chengdong Wu
    • 1
  • Yunzhou Zhang
    • 1
  • Hao Chu
    • 1
  • He Teng
    • 1
  1. 1.Faculty of Robot Science and EngineeringNortheastern UniversityShenyangChina

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