Skip to main content
SpringerLink
Log in

Probabilistic coverage in directional sensor networks

  • Published:
Wireless Networks Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Ahmed, N., Kanhere, S., & Jha, S. (2005). Probabilistic coverage in wireless sensor networks. In Proceedings of the IEEE LCN.

  2. Akyildiz, I. F., Pompili, D., & Melodia, T. (2005). Underwater acoustic sensor networks: Research challenges. Ad Hoc Networks, 3(3), 257–279.

    Article  Google Scholar 

  3. Akyildiz, I. F., Melodia, T., & Chowdhury, K. R. (2007). A survey on wireless multimedia sensor networks. Computer Networks, 51(4), 921–960.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  MathSciNet  MATH  Google Scholar 

  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.

    Article  Google Scholar 

  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. Guvensan, M. A., & Yavuz, A. G. (2011). On coverage issues in directional sensor networks: A survey. Ad Hoc Networks, 9(7), 1238–1255.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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. 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).

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  19. Ma, H., & Liu, Y. (2007). Some problems of directional sensor networks. International Journal of Sensor Networks, 2(1/2), 44–52.

    Article  Google Scholar 

  20. Ma, H., Zhang, X., & Ming, A. (2009). A coverage-enhancing method for 3D directional sensor networks. In Proceedings of the IEEE INFOCOM.

  21. Meguerdichian, S., Koushanfar, F., Potkonjak, M., & Srivastava, M. (2001). Coverage problems in wireless ad-hoc sensor networks. In Proceedings of the IEEE INFOCOM.

  22. Onur, E., Ersoy, C., & Deliç, H. (2006). How many sensors for an acceptable breach detection probability? Computer Communications, 29(2), 173–182.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  MathSciNet  MATH  Google Scholar 

  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.

Download references

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).

Author information

Authors and Affiliations

  1. Faculty of Robot Science and Engineering, Northeastern University, Shenyang, 110819, China

    Pengju Si, Chengdong Wu, Yunzhou Zhang, Hao Chu & He Teng

Authors
  1. Pengju Si
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chengdong Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yunzhou Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hao Chu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. He Teng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pengju Si.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Si, P., Wu, C., Zhang, Y. et al. Probabilistic coverage in directional sensor networks. Wireless Netw 25, 355–365 (2019). https://doi.org/10.1007/s11276-017-1564-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-017-1564-4

Keywords

Search

Navigation