Abstract
The fundamental issue in sensor networks is providing a certain degree of coverage and maintaining connectivity under the energy constraint. In this paper, the connected k-coverage problem is investigated under the probabilistic sensing and communication models, which are more realistic than deterministic models. Furthermore, different weights for nodes are added in order to estimate the real power consumption. Because the problem is NP-hard, a distributed probabilistic coverage and connectivity maintenance algorithm (DPCCM) for dense sensor networks is proposed. DPCCM converts task requirement into two parameters by using the consequence of Chebyshev’s inequality, then activate sensors based on the properties of weighted ε-net. It is proved that the sensors chosen by DPCCM have (θ,k)-coverage and α-connectivity. And the time and communication complexities are theoretically analyzed. Simulation results show that compared with the distributed randomized k-coverage algorithm, DPCCM significantly maintain coverage in probabilistic model and prolong the network lifetime in some sense.
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Estrin, D., Govindan, R., Heidemann, J., Kumar, S.: Next century challenges: Scalable coordination in sensor networks. In: 5th ACM International Conference on Mobile Computing and Networking (MOBICOM 1999), pp. 263–270. ACM Press, Seattle (1999)
Cerpa, A., Elson, J., Hamilton, M., Zhao, J., Estrin, D., Girod, L.: Habitat monitoring: Application driver for wireless communications technology. In: Proc. of ACM SIGCOMM Workshop on Data Communications in Latin America and the Caribbean, pp. 3–5. ACM Press, Costa Rica (2001)
Akyildiz, I., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: A survey. Computer Networks 38(4), 393–422 (2002)
Yang, S., Dai, F., Cardei, M., Wu, J., Patterson, F.: On connected multiple point coverage in wireless sensor networks. Journal of Wireless Information Networks 13(4), 289–301 (2006)
Hekmat, R., Van Mieghem, P.: Connectivity in wireless ad-hoc networks with a log-normal radio model. Mobile Networks and Applications 11(3), 351–360 (2006)
Hefeeda, M., Ahmadi, H.: A probabilistic coverage protocol for wireless sensor networks. In: 15th IEEE International Conference on Network Protocols (ICNP 2007), pp. 41–50. IEEE Press, Beijing (2007)
Hefeeda, M., Bagheri, M.: Randomized k-coverage algorithms for dense sensor networks. In: 26th IEEE International Conference on Computer Communications (INFOCOM 2007), pp. 2376–2380. IEEE Press, Anchorage (2007)
Chakrabarty, K., Iyengar, S., Qi, H., Cho, E.: Grid coverage for surveillance and target location in distributed sensor networks. IEEE Transactions on Computers 51(12), 1448–1453 (2002)
Huang, C., Tseng, Y.: The coverage problem in a wireless sensor network. In: 2nd ACM International Conference on Wireless Sensor Networks and Applications (WSNA 2003), pp. 115–121. ACM Press, San Diego (2003)
Zhou, Z., Das, S., Gupta, H.: Connected k-coverage problem in sensor networks. In: 13th International Conference on Computer Communications and Networks (ICCCN 2004), pp. 373–378. IEEE Press, Chicago (2004)
Wu, J., Dai, F.: On constructing k-connected k-dominating set in wireless networks. In: 19th International Parallel and Distributed Processing Symposium (IPDPS 2005), pp. 81a–81a. IEEE Press, Denver (2005)
Lu, J., Bao, L., Suda, T.: Coverage-Aware Sensor Engagement in Dense Sensor Networks. In: Yang, L.T., Amamiya, M., Liu, Z., Guo, M., Rammig, F.J. (eds.) EUC 2005. LNCS, vol. 3824, pp. 639–650. Springer, Heidelberg (2005)
Hefeeda, M., Ahmadi, H.: Network connectivity under probabilistic communication models in wireless sensor networks. In: 4th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS 2007), pp. 1–9. IEEE Press, Pisa (2007)
He, T., Huang, C., Lum, B., Stankovic, J., Adelzaher, T.: Range-free localization schemes for large scale sensor networks. In: 9th ACM International Conference on Mobile Computing and Networking (MOBICOM 2003), pp. 81–95. ACM Press, San Diego (2003)
Ganeriwal, S., Kumar, R., Srivastava, M.B.: Network-Wide Time Synchronization in Sensor Networks. NESL Technical Report (2003)
Gupta, H., Zhou, Z., Das, S.R., Gu, Q.: Connected sensor cover: Self-Organization of sensor networks for efficient query execution. In: 4th ACM Interational Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc 2003), pp. 189–200. ACM Press, New York (2003)
Brönnimann, H., Goodrich, M.: Almost optimal set covers in finite VC-dimension. Discrete&Computational Geometry 14(4), 463–479 (1995)
Haussler, D., Welzl, E.: Epsilon-nets and simplex range queries. Discrete and Computational Geometry 2(1), 127–151 (1987)
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Wu, Y., Li, M., Cai, Z., Zhu, E. (2008). A Distributed Algorithm to Approximate Node-Weighted Minimum α-Connected (θ,k)-Coverage in Dense Sensor Networks. In: Preparata, F.P., Wu, X., Yin, J. (eds) Frontiers in Algorithmics. FAW 2008. Lecture Notes in Computer Science, vol 5059. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69311-6_24
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DOI: https://doi.org/10.1007/978-3-540-69311-6_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69310-9
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