ADHOCNETS 2015: Ad Hoc Networks pp 245-254 | Cite as

A Low-Overhead Localized Target Coverage Algorithm in Wireless Sensor Networks

Conference paper
First Online:
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 140)

Abstract

The scope of this paper is to present a low-overhead localized algorithm for the target coverage problem in wireless sensor networks. The algorithm divides the sensors into active and sleep mode nodes in order to conserve energy and extend the network lifetime. The set of active mode nodes provide full coverage to a set of targets (points) in the field. The decision of which sensors will remain active at any time is locally taken by the nodes by exchanging messages with each other. This kind of messages add overhead in the network, while high overhead can dramatically decrease the network lifetime especially in case of high node density environments. To tackle this problem we propose two variations of a localized algorithm with low communication complexity. Finally, the operational effectiveness of the proposed approaches is evaluated through simulation, while their superiority against other relevant proposed solutions in the literature is illustrated. The results show a great improvement in terms of communication cost while achieving an adequate network lifetime.

Keywords

Sensor Node Wireless Sensor Network Network Lifetime Active Node Coverage Status 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Deak, G., Curran, K., Condell, J.: A survey of active and passive indoor localisation systems. Computer Communications 35(16), 1939–1954 (2012)CrossRefGoogle Scholar
  2. 2.
    Liu, Y., Yang, Z., Wang, X., Jian, L.: Location, localization, and localizability. Journal of Computer Science and Technology 25(2), 274–297 (2010)CrossRefGoogle Scholar
  3. 3.
    Cardei, M., Thai, M., Li, Y., Wu, W.: Energy-efficient target coverage in wireless sensor networks. In: Proc. of INFOCOM 2005, vol. 3, pp. 1976–1984. IEEE (March 2005).Google Scholar
  4. 4.
    Luo, W., Wang, J., Guo, J., Chen, J.: Parameterized complexity of max-lifetime target coverage in wireless sensor networks. Theoretical Computer Science 518, 32–41 (2014)CrossRefMATHMathSciNetGoogle Scholar
  5. 5.
    Gu, Y., Zhao, B.H., Ji, Y.S., Li, J.: Theoretical treatment of target coverage in wireless sensor networks. Journal of Computer Science and Technology 26(1), 117–129 (2011)CrossRefMATHGoogle Scholar
  6. 6.
    Mostafaei, H., Meybodi, M.: Maximizing lifetime of target coverage in wireless sensor networks using learning automata. Wireless Personal Communications 71(2), 1461–1477 (2013)CrossRefGoogle Scholar
  7. 7.
    Ding, L., Wu, W., Willson, J., Wu, L., Lu, Z., Lee, W.: Constant-approximation for target coverage problem in wireless sensor networks. In: INFOCOM, 2012 Proceedings IEEE, pp. 1584–1592 (March 2012).Google Scholar
  8. 8.
    Cheng, M., Gong, X.: Maximum lifetime coverage preserving scheduling algorithms in sensor networks. Journal of Global Optimization 51(3), 447–462 (2011)CrossRefMATHGoogle Scholar
  9. 9.
    Ding, Y.S., Lu, X.J., Hao, K.R., Li, L.F., Hu, Y.F.: Target coverage optimisation of wireless sensor networks using a multi-objective immune co-evolutionary algorithm. Intern. J. Syst. Sci. 42(9), 1531–1541 (2011)CrossRefMATHMathSciNetGoogle Scholar
  10. 10.
    Gil, J.M., Han, Y.H.: A target coverage scheduling scheme based on genetic algorithms in directional sensor networks. Sensors 11(2), 1888–1906 (2011)CrossRefGoogle Scholar
  11. 11.
    Zorbas, D., Glynos, D., Kotzanikolaou, P., Douligeris, C.: Solving coverage problems in wireless sensor networks using cover sets. Ad Hoc Networks 8, 400–415 (2010)CrossRefGoogle Scholar
  12. 12.
    Hongwu, Z., Hongyuan, W., Hongcai, F., Bing, L., Bingxiang, G.: A heuristic greedy optimum algorithm for target coverage in wireless sensor networks. In: Pacific-Asia Conference on Circuits, Communications and Systems, pp. 39–42 (2009).Google Scholar
  13. 13.
    He, J., Xiong, N., Xiao, Y., Pan, Y.: A reliable energy efficient algorithm for target coverage in wireless sensor networks. In: 2010 IEEE 30th International Conference on Distributed Computing Systems Workshops (ICDCSW), pp. 180–188 (June 2010).Google Scholar
  14. 14.
    Zhao, Q., Gurusamy, M.: Lifetime maximization for connected target coverage in wireless sensor networks. IEEE/ACM Trans. Netw. 16(6), 1378–1391 (2008)CrossRefGoogle Scholar
  15. 15.
    Zorbas, D., Douligeris, C.: Connected coverage in wsns based on critical targets. Computer Networks 55(6), 1412–1425 (2011)CrossRefGoogle Scholar
  16. 16.
    Zhao, Q., Gurusamy, M.: Connected k-target coverage problem in wireless sensor networks with different observation scenarios. Comput. Netw. 52(11), 2205–2220 (2008)CrossRefMATHGoogle Scholar
  17. 17.
    Zhang, H., Wang, H., Feng, H.: A distributed optimum algorithm for target coverage in wireless sensor networks. In: Asia-Pacific Conference on Information Processing, APCIP 2009, vol. 2, pp. 144–147(July 2009).Google Scholar
  18. 18.
    Guo, P., Jiang, T., Zhang, Q., Zhang, K.: Sleep scheduling for critical event monitoring in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems 23(2), 345–352 (2012)CrossRefGoogle Scholar
  19. 19.
    Bulut, E., Korpeoglu, I.: Sleep scheduling with expected common coverage in wireless sensor networks. Wireless Networks 17(1), 19–40 (2011)CrossRefGoogle Scholar
  20. 20.
    Nan, G., Shi, G., Mao, Z., Li, M.: Cdsws: coverage-guaranteed distributed sleep/wake scheduling for wireless sensor networks. EURASIP Journal on Wireless Communications and Networking 2012(1) (2012).Google Scholar
  21. 21.
    Slijepcevic, S., Potkonjak, M.: Power efficient organization of wireless sensor networks. In: Proc. of International Conference on Communications (ICC 2001), pp. 472–476. IEEE (June 2001).Google Scholar
  22. 22.

Copyright information

© Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014

Authors and Affiliations

  1. 1.Inria LilleNord EuropeFrance
  2. 2.Department of InformaticsUniversity of PiraeusPiraeusGreece

Personalised recommendations