Nodes self-scheduling approach for maximising wireless sensor network lifetime based on remaining energy

Nodes self-scheduling approach for maximising wireless sensor network lifetime based on remaining energy

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Wireless Sensor Systems — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Coverage and energy conservation are two major issues in wireless sensor networks (WSNs), especially when sensors are randomly deployed in large areas. In such WSNs, sensors are equipped with limited lifetime batteries and redundantly cover the target area. To face the short lifetime of the WSN, the objective is to optimise energy consumption while maintaining the full sensing coverage. A major technique to save the energy is to use a wake-up scheduling protocol through which some nodes stay active whereas the others enter sleep state so as to conserve their energy. This study presents an original algorithm for node selfscheduling to decide which ones have to switch to the sleep state. The novelty is to take into account the remaining energy at every node in the decision of turning off redundant nodes. Hence, the node with a low remaining energy has priority over its neighbours to enter sleep state. The decision is based on a local neighbourhood knowledge that minimises the algorithm overhead. To verify and evaluate the proposed algorithm, simulations have been conducted and have shown that it can contribute to extend the network lifetime. A comparison with existing works is also presented and the performance gains are highlighted.


    1. 1)
      • S. Arms Chris Townsend , J.S. Wilson . (2004) Wireless sensor networks: principles and applications, Sensor technology handbook.
    2. 2)
      • Meguerdichian, S., Koushanfar, F., Potkonjak, M., Srivastava, M.B.: `Coverage problems in wireless ad-hoc sensor networks', INFOCOM 2001: 20th Annual Joint Conf. IEEE Computer and Communications Societies, 2001, p. 1380–1387, vol. 3.
    3. 3)
    4. 4)
      • Ammari, H.M., Giudici, J.: `On the connected k-coverage problem in heterogeneous sensor nets: the curse of randomness and heterogeneity', ICDCS '09: Proc. 2009 29th IEEE Int. Conf. on Distributed Computing Systems, 2009, p. 265–272.
    5. 5)
    6. 6)
    7. 7)
      • Chang, J.-H., Tassiulas, L.: `Energy conserving routing in wireless ad-hoc networks', INFOCOM 2000: 19th Annual Joint Conf. IEEE Computer and Communications Societies, 2000, p. 22–31.
    8. 8)
      • Zhang, H., Wang, H., Feng, H.: `A distributed optimum algorithm for target coverage in wireless sensor networks', Asia-Pacific Conf. on Information Processing, 2009, p. 144–147.
    9. 9)
      • Chen, A.: `Designing localized algorithms for barrier coverage', Proc. ACM MobiCom'07, 2007.
    10. 10)
      • Osmani, A., Dehghan, M., Pourakbar, H., Emdadi, P.: `Fuzzy-based movement-assisted sensor deployment method in wireless sensor networks', Int. Conf. on Computational Intelligence, Communication Systems and Networks, 2009, p. 90–95.
    11. 11)
      • Cardei, M., Thai, M.T., Yingshu, L., Weili, W.: `Energy-efficient target coverage in wireless sensor networks', INFOCOM 2005: 24th Annual Joint Conf. IEEE Computer and Communications Societies, 2005, p. 1976–1984, vol. 3.
    12. 12)
      • Slijepcevic, S., Potkonjak, M.: `Power efficient organization of wireless sensor networks', ICC 2001: IEEE Int. Conf. on Communications, 2001, p. 472–476.
    13. 13)
      • Tian, D., Georganas, N.D.: `A coverage-preserving node scheduling scheme for large wireless sensor networks', WSNA'02: Proc. First ACM Int. Workshop on Wireless Sensor Networks and Applications, 2002, p. 32–41.
    14. 14)
      • Ye, F., Zhong, G., Lu, S., Zhang, L.: `Peas: a robust energy conserving protocol for long-lived sensor networks', Proc. of Int. Conf. on Distributed Computing Systems (ICDCS), 2002, p. 28–37.
    15. 15)
      • Chih-fan, H., Mingyan, L.: `Network coverage using low duty-cycled sensors: random & coordinated sleep algorithms', IPSN'04: Proc. Third Int. Symp. on Information Processing in Sensor Networks, 2004, p. 433–442.
    16. 16)
    17. 17)
      • Ali Raza Zaidi, S., Hafeez, M., McLernon, D.C., Ghogho, M.: `A probabilistic model of k-coverage in minimum cost wireless sensor networks', CONEXT '08: Proc. 2008 ACM CoNEXT Conf., 2008, p. 1–2.
    18. 18)
      • M. Hefeeda , H. Ahmad . An integrated protocol for maintaining connectivity and coverage under probabilistic models for wireless sensor network. Ad Hoc Sens. Wirel. Netw. , 295 - 323
    19. 19)
      • Ammari, H.M.: `Stochastic k-coverage in wireless sensor networks', WASA'09: Proc. Fourth Int. Conf. on Wireless Algorithms, Systems, and Applications, 2009, p. 125–134.
    20. 20)
    21. 21)
      • Gao, S., Wang, X., Li, Y.: `p-percent coverage schedule in wireless sensor networks', ICCCN'08: 17th Int. Conf. on Computer Communications and Networks, 2008, p. 1–6.
    22. 22)
    23. 23)
    24. 24)
      • R. Mulligan . Coverage in wireless sensor networks: a survey. Netw. Protocols Algorithms , 27 - 53
    25. 25)
      • Gurun, S., Krintz, C.: `A run-ti feedback-based energy estimation model for embedded devices', Proc. Fourth Int. Conf. on Hardware/Software Codesign and System Synthesis, 2006, p. 28–33.
    26. 26)
      • Anh Nguyen, H., Frster, A., Puccinelli, D., Giordano, S.: `Sensor node lifetime: an experimental study', PerCom Workshops'11, 2011, p. 202–207.
    27. 27)
    28. 28)
      • Huang, D.-F., Tseng, Y.-C.: `The coverage problem in a wireless sensor network', WSNA'03: Proc. Second ACM Int. Conf. on Wireless Sensor Networks and Applications, 2003, p. 115–121.
    29. 29)
      • Huang, C.-F., Tseng, Y.-C., Lo, L.-C.: `The coverage problem in three-dimensional wireless sensor networks', GLOBECOM'04: IEEE Global Telecommunications Conf., 2004, p. 3182–3186.
    30. 30)
    31. 31)
      • P. Levis , S. Madden , J. Polastre , W. Werner . (2004) TinyOS: an operating system for sensor networks, Ambient intelligence.

Related content

This is a required field
Please enter a valid email address