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Energy-Efficient Connected Target Coverage in Multi-hop Wireless Sensor Networks

  • Swagata BiswasEmail author
  • Ria Das
  • Punyasha Chatterjee
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 11)

Abstract

Wireless sensor networks (WSNs) employ numerous sensor nodes possessing sensing, processing, and wireless communication abilities to monitor a specified sensing field. As sensor nodes are mostly battery operated and are highly constrained regarding energy resources, it is essential to explore energy optimization methods to prolong WSN lifetime. Target tracking is a very conventional WSN application that demands both useful and coherent energy management. This paper proposes a distributed shortest path data collection algorithm for connected target coverage to maximize WSN lifetime pertaining to both static and mobile multi-hop WSNs. The performance is evaluated in TinyOS employing the TOSSIM simulator based on the parameters like percentage of alive nodes, load distribution of nodes, and network lifetime.

Keywords

Wireless sensor network Target coverage Energy-efficient Network lifetime 

References

  1. 1.
    Huang, C.F., Tseng, Y.C.: A survey of solutions to the coverage problems in wireless sensor networks. J. Int. Technol. 6, 1–8 (2005)Google Scholar
  2. 2.
    Carle, J., Simplot, D.: Energy efficient area monitoring by sensor networks. IEEE Comput. 37(2), 40–46 (2004)CrossRefGoogle Scholar
  3. 3.
    Wang, J., Niu, C., She, R.: Priority-based target coverage in directional sensor networks using a genetic algorithm. Comput. Math. Appl. 57(11/12), 1915–1922 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Li, X.-Y., Wan, P.-J., Frieder, O.: Coverage in wireless adhoc sensor networks. IEEE Trans. Comput. 52, 753–763 (2002)Google Scholar
  5. 5.
    Lu, M., et al.: Energy-efficient connected coverage of discrete targets in wireless sensor networks. ICCNMC 2005. LNCS 3619, 4352 (2005)Google Scholar
  6. 6.
    Zhao, Q., Gurusamy, M.: Lifetime maximization for connected target coverage in wireless sensor networks. IEEE/ACM Trans. Netw. 16(6), 13781391 (2008b)Google Scholar
  7. 7.
    Farooq, M.O., Kunz, T.: Operating systems for wireless sensor networks: a survey. Sensors 11, 5900–5930 (2011)Google Scholar
  8. 8.
    Levis, P., et al.: TOSSIM: a simulator for TinyOS networks, Version 1.0, June 26, 2003Google Scholar
  9. 9.
    Pyun, S.-Y., et al.: Power-saving scheduling for multiple-target coverage in wireless sensor networks. IEEE Commun. Lett. 13(2) (2009)Google Scholar
  10. 10.
    Jamali, et al.: An energy-efficient algorithm for connected target coverage problem in wireless sensor networks. 978-1-4244-5540-9/10Google Scholar
  11. 11.
    Manju Pujari, A.K.: High-energy-first (HEF) heuristic for energy-efficient target coverage problem. Int. J. Ad Hoc Sens. Ubiquitous Comput. (IJASUC) 2(1) (2011)Google Scholar
  12. 12.
    Gil, J.-M., et al.: A target coverage scheduling scheme based on genetic algorithms in directional sensor networks. Sensors 11, 1888–1906 (2011)CrossRefGoogle Scholar
  13. 13.
    Tan, R., et al.: Exploiting reactive mobility for collaborative target detection in wireless sensor networks. IEEE Trans. Mobile Comput. 9(3) (2010)Google Scholar
  14. 14.
    Xiao, Y., et al.: A reliable energy efficient algorithm for target coverage in wireless sensor networks. In: 2010 IEEE 30th International Conference on Distributed Computing Systems WorkshopsGoogle Scholar
  15. 15.
    Zhang, H., Hou, J.: Maintaining sensing coverage and connectivity in large sensor networks. Ad Hoc Sens. Wireless Netw. 1(1–2) (2005)Google Scholar
  16. 16.
    Tian, D., Georganas, N.: A coverage-preserving node scheduling scheme for large wireless sensor networks. In: Proceedings of the 1st ACM Workshop on Wireless Sensor Networks and Applications (2002)Google Scholar
  17. 17.
    Alagu Pushpa, R., et al.: Impact of mobility models on mobile sensor networks. Int. J. Commun. Netw. Secu. 1(1) (2011)Google Scholar
  18. 18.
    Villas, L.A., et al.: DRINA: a lightweight and reliable routing approach for in-network aggregation in wireless sensor networks. IEEE Trans. Comput. 62(4) (2013)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.School of Mobile Computing and CommunicationJadavpur UniversityKolkataIndia

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