Wireless Personal Communications

, Volume 96, Issue 2, pp 3159–3178 | Cite as

SPMI: Single Phase Multiple Initiator Protocol for Coverage in Wireless Sensor Networks

  • Abdelkader Khelil
  • Rachid Beghdad


Even if several algorithms were proposed in the literature to solve the coverage problem in wireless sensor networks (WSNs), they still suffer from some weaknesses. This is the reason why we suggest in this paper, a distributed protocol, called single phase multiple initiator (SPMI). Its aim is to find connect cover set for assuring the coverage and connectivity in WSN. Our idea is based on determining a connected dominating set (CDS) which has a minimum number of necessary and sufficient nodes to guarantee coverage of the area of interested (AI), when WSN model is considered as a graph. The suggested protocol only requires a single phase to construct a CDS in distributed manner without using sensors’ location information. Simulation results show that SPMI assures better coverage and connectivity of AI by using fewer active nodes and by inducing very low message overhead, and low energy consumption, when compared with some existing protocols. Finally, we’ve presented an analytical model of SPMI, which is based on Markov’s chains.


Wireless sensor network (WSNCoverage Connectivity Distributed algorithm Connected dominating set (CDS


  1. 1.
    Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks Journal, 38(4), 393–422.CrossRefGoogle Scholar
  2. 2.
    Huang, C. F., & Tseng, Y. C. (2005). A survey of solutions to the coverage problems in wireless sensor networks. Journal of Internet Technology, 6(1), 1–8.Google Scholar
  3. 3.
    Cardei, M., & Wu, J. (2006). Energy-efficient coverage problems in wireless ad hoc sensor networks. Computer Communications Journal, 29(4), 413–420.CrossRefGoogle Scholar
  4. 4.
    Meguerdichian, S., Koushanfar, F., Potkonjak, M., & Srivastava, M. B. (2001). Coverage problems in wireless ad-hoc sensor networks. In 20th annual joint conference of the IEEE computer and communications societies (Vol. 3, pp. 1380–1387).Google Scholar
  5. 5.
    Rajavavivarme, V., Yang, Y., & Yang, T. (2003). An overview of wireless sensor network and applications. In Proceedings of the 35th southeastern symposium on system theory, pp. 432–436, March 2003.Google Scholar
  6. 6.
    Khelil, A., & Beghdad, R. (2012). Coverage and connectivity protocol for wireless sensor networks. In Proceedings of the 24th international conference of microelectronics ICM 2012, December 17–20, 2012, Algeria.Google Scholar
  7. 7.
    Pazand, B., & Datta, A. (2006). Minimum dominating sets for solving the coverage problem in wireless sensor networks. In Proceedings of the international symposium on ubiquitous computing systems (pp. 454–466).Google Scholar
  8. 8.
    Wu, J., Cardei, M., Dai, F., & Yang, S. (2006). Extended dominating set and its applications in ad hoc networks using cooperative communication. IEEE Transactions on Parallel and Distributed Systems, 17(8), 851–864.CrossRefGoogle Scholar
  9. 9.
    Yuanyuan, Z., Jia, X., & Yanxiang, H. (2006). Energy efficient distributed connected dominating sets construction in wireless sensor networks. In Proceedings of the ACM international conference on communications and mobile computing (pp. 797–802).Google Scholar
  10. 10.
    Wightman, P. M., & Labrador, M. A. (2008). A3: A topology construction algorithm for wireless sensor network. In Proceedings of IEEE Globecom, 2008.Google Scholar
  11. 11.
    Karthikeyan, A., Shankar, T., Srividhya, V., Reddy, S. C., & Kommineni, S. (2013). Topology control algorithm for better sensing coverage with connectivity in WSN. Journal of Theoretical and Applied Information Technology, 52(3), 308–316.Google Scholar
  12. 12.
    Shi, T., Shi, X., & Fang, X. (2014) A virtual backbone construction algorithm based on connected dominating set in wireless sensor networks. In Proceedings of the 2014 international conference on computer, communications and information technology (CCIT) 2014.Google Scholar
  13. 13.
    Pu, C.-C., & Chung, W.-Y. (2008). Mitigation of multipath fading effects to improve indoor RSSI performance. IEEE Sensors Journal, 8(11), 1884–1886.CrossRefGoogle Scholar
  14. 14.
    Hood, B., & Barooah, P. (2011). Estimating DoA from radio-frequency RSSI measurements using an actuated reflector. IEEE Sensors Journal, 11(2), 413–417.CrossRefGoogle Scholar
  15. 15.
    MICA2 Mote Datasheet. Available from Crossbow Technology Inc., 2009.
  16. 16.
    Ye, F., Zhang, H., Lu, S., Zhang, L., & Hou, J. (2006). A randomized energy-conservation protocol for resilient sensor networks. Wireless Networks, 12(5), 637–652.CrossRefGoogle Scholar
  17. 17.
    Anastasi, G., Falchi, A., Passarella, A., Conti, M., & Gregori, E. (2004). Performance measurements of motes sensor networks. In Proceedings of the 7th ACM international symposium on modeling, analysis and simulation of wireless and mobile systems (pp. 174–181).Google Scholar
  18. 18.
    Carle, J., Gallais, A., & Simplot-Ryl, D. (2005). Preserving area coverage in wireless sensor networks by using surface coverage relay dominating sets. In Proceedings of 10th IEEE Symposium on Computers and Communications (pp. 347–352).Google Scholar
  19. 19.
    Khanouche, M. E. (2010). Traitement du problème de couverture dans les réseaux de capteurs sans fil, mémoire de Magistère, université de béjaia, Algérie.Google Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Faculty of SciencesZiane Achour UniversityDjelfaAlgeria
  2. 2.Faculty of SciencesAbderrahmane Mira UniversityBéjaïaAlgeria

Personalised recommendations