Skip to main content
Journal of the Brazilian Computer Society
Download PDF

Application oriented connected dominating set-based cluster formation in wireless sensor networks

Journal of the Brazilian Computer Society volume 17, pages 3–18 (2011)Cite this article

Abstract

Clustering is a fundamental mechanism used in the design of Wireless Sensor Network (WSN) protocols. The performance of WSNs can be improved by selecting the most suitable nodes to form a stable backbone structure with guaranteed network coverage. This paper proposes a base station-controlled centralized algorithm for static sensor networks and a distributed, weighted algorithm for dynamic sensor networks. The solutions are based on a (k,r)-Connected Dominating Set, which is suitable for cluster-based hierarchical routing. The clusterhead redundancy parameter k improves reliability, the multi-hop parameter r addresses the scalability issue and the combined weight metric improves the network lifespan and reduces the number of re-affiliations. To create a stable and efficient backbone structure, the backbone sensor nodes are selected based on quality, which is a function of the residual battery power, node degree, transmission range, and mobility of the sensor nodes. Simulation experiments are conducted to evaluate the performance of both the algorithms in terms of the number of elements in the backbone structure, re-affiliation frequency, load balancing, network lifespan, and the power dissipation. The results establish the potential of these algorithms for use in WSNs.

References

  1. 1.

    Agre J, Clare L (2000) An integrated architecture for cooperative sensing networks. Computer 33(5):106–108

    Article  Google Scholar 

  2. 2.

    Akkaya K, Younis M (2005) A survey on routing protocols for wireless sensor networks. Ad Hoc Netw 3(3):325–349

    Article  Google Scholar 

  3. 3.

    Akyildiz IF, Su W, Sankaraubramaniam Y, Cayirci E (2002) A survey on sensor networks. IEEE Commun Mag

  4. 4.

    Akylidiz IF, Su W, Sankarasubramanian Y, Cayirci E (2002) Wireless sensor network: A survey on sensor network. IEEE Commun Mag 40(8):102–114

    Article  Google Scholar 

  5. 5.

    Anitha VS, Sebastian MP (2009) Scenario-based cluster formationand management in mobile ad hoc networks. Int J Mobile Comput Multimedia Commun 1(1):1–15 (IGI Journal)

    Article  Google Scholar 

  6. 6.

    Anitha VS, Sebastian MP (2009) Scenario-based diameter-bounded algorithm for cluster creation and management in mobile ad hoc networks. In: 13th IEEE/ACM international symposium on distributed simulation and real time applications, pp 97–104

    Google Scholar 

  7. 7.

    Blum J, Ding M, Thaeler A, Cheng X (2004) Connected dominating set in sensor networks and MANETs. In: Du D-Z, Pardalos P (eds) Handbook of combinatorial optimization. Kluwer Academic, Amsterdam

    Google Scholar 

  8. 8.

    Bonnet P, Gehrke J, Seshadri P (2000) Querying the physical world. IEEE Pers Commun 7(5):10–15

    Article  Google Scholar 

  9. 9.

    Bulusu N, Estrin D, Girod L, Heidemann J (2001) Scalable coordination for wireless sensor networks: self-configuring localization systems. In: International symposium on communication theory and applications (ISCTA 2001). Ambleside, UK, 2001

    Google Scholar 

  10. 10.

    Buratti C, Conti A, Dardari D, Verdone R (2009) An overview on wireless sensor networks technology and evolution. Sensors 9(9):6869–6896

    Article  Google Scholar 

  11. 11.

    Chatterjee M, Das SK, Turgut D (2002) Wca: a weighted clustering algorithm for mobile ad hoc networks. Clust Comput 5(1):193–204

    Article  Google Scholar 

  12. 12.

    Chen Y, Lieshman AL (2002) Approximating minimum size weakly connected dominating sets for clustering mobile ad hoc networks. In: MobiHoc. ACM Press, New York, pp 165–172

    Google Scholar 

  13. 13.

    Das B, Bhargavan V (1997) Routing in ad hoc networks using minimum connected dominating set. In: ICE, pp 371–380

    Google Scholar 

  14. 14.

    Das B, Sivakumar E, Bhargavan V (1997) Routing in ad hoc networks using a virtual backbone. In: Proceedings for the 6th international conference on computer communications and networks (IC3N’97), Las Vegas, NV, USA, 1997, pp 22–25

    Google Scholar 

  15. 15.

    Das B, Sivakumar R, Bharghavan V (1997) Routing in ad-hoc networks using a spine. In: Proc of international conference on computers and communications networks, ICCCN, Las Vegas, 1997

    Google Scholar 

  16. 16.

    Ding P, Holliday J, Celek A (2005) Distributed energy efficient hierarchical clustering for wireless sensor networks. In: Proc of the IEEE international conference on distributed computing in sensor systems

    Google Scholar 

  17. 17.

    Friis: (1946) A note on simple transmission formula. In: Proceedings of IRE, pp 254–256

    Google Scholar 

  18. 18.

    Garey M, Johnson D (1978) Computers and intractability: a guide to NP-completeness

  19. 19.

    Guha S, Khuller S (1998) Approximation algorithms for connected dominating sets. Algorithmica 20:374–387

    MathSciNet  Article  Google Scholar 

  20. 20.

    Halweil B (2001) Study finds modern farming is costly. World Watch 14(1):9–10

    Google Scholar 

  21. 21.

    Heinzelman W, Chandrakasan A, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 1(4):660–670

    Article  Google Scholar 

  22. 22.

    Johnson P, Andrews DC (1996) Remote continuous physiological monitoring in the home. J Telemed Telecare 2(2):107–113

    Article  Google Scholar 

  23. 23.

    Kahn J, Katz R, Pister K (1999) Next century challenges: mobile networking for smart dust. In: Proceedings of the ACM MobiCom’99. Washington, USA, 1999, pp 271–278

    Google Scholar 

  24. 24.

    Li J, Andrew LL, Foh CH, Zukerman M, Chen HH (2009) Connectivity, coverage and placement in wireless sensor networks. Sensors

  25. 25.

    Lindsey S, Raghavendra CS (2002) Pegasis: power efficient gathering in sensor information systems. In: Proc of IEEE aerospace conference. IEEE

    Google Scholar 

  26. 26.

    Noury N, Herve T, Rialle V, Virone G, Mercier E, Morey G, Moro A, Porcheron T (2000) Monitoring behavior in home using a smart fall sensor. In: IEEE-EMBS special topic conference on microtechnologies in medicine and biology, pp 607–610

    Google Scholar 

  27. 27.

    Paruchuri V, Durresi A, Durresi M, Barolli L (2005) Routing through back bone structures in sensor networks. In: Proceedings ICPADS, ICPADS, Japan, 2005, pp 397–401

    Google Scholar 

  28. 28.

    Rabaey J, Ammer M, da Silva J Jr, Patel D, Roundy S (2000) Picoradio supports ad hoc ultra-low power wireless networking. IEEE Comput Mag

  29. 29.

    Ryl DS, Stojmenovic I, Wu J (2005) Energy-efficient backbone construction, broadcasting, and area coverage in sensor networks. Handbook of sensor networks. Wiley, New York

    Google Scholar 

  30. 30.

    Sinha P, Sivakumar R, Bharghavan V (2001) Enhancing ad hoc routing with dynamic virtual infrastructures. In: 20th annual joint conference of the IEEE computer and communications societies, vol 3

    Google Scholar 

  31. 31.

    Stojmenovic I, Wu J (2004) Broadcasting and activity scheduling in AD HOC networks. In: Basagni S, Conti M, Giordano S, Stojmenovic I (eds) Mobile ad hoc networking. IEEE, New York

    Google Scholar 

  32. 32.

    Wan PJ, Alzoubi KM, Frieder O (2004) Distributed construction of connected dominating set in wireless ad hoc networks. Mobile Netw Appl 9:141–149

    Article  Google Scholar 

  33. 33.

    Warneke B, Liebowitz B, Pister K (2001) Smart dust: communicating with a cubic-millimeter computer. IEEE Computer, New York

    Google Scholar 

  34. 34.

    Wu J, Li H On calculating connected dominating set for efficient routing in ad hoc wireless networks. In: Proc of proceedings of the 3rd ACM international workshop on discrete algorithms and methods for mobile computing and communications, pp. 7–14. ACM, New York

  35. 35.

    Wu Y, Li Y (2008) Construction algorithms for k-connected m-dominating sets in wireless sensor networks. In: Mobihoc 2008

    Google Scholar 

  36. 36.

    Wu Y, Wang F, Thai MT, Li Y (2007) Constructing k-connected m-dominating sets in wireless sensor networks. In: Military communications conference. MILCOM, Orlando, pp 29–31

    Google Scholar 

  37. 37.

    Younis O, Fahmy S (2004) Heed: A hybrid energy-efficient distributed clustering approach for ad hoc sensor networks. IEEE Trans Mob Comput 3(4):366–379

    Article  Google Scholar 

Download references

Author information

Affiliations

  1. National Institute of Technology, Calicut, Kerala, India

    V. S. Anitha

  2. Indian Institute of Management Kozhikode, Kozhikode, Kerala, India

    M. P. Sebastian

Authors
  1. V. S. Anitha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. P. Sebastian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to V. S. Anitha.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Anitha, V.S., Sebastian, M.P. Application oriented connected dominating set-based cluster formation in wireless sensor networks. J Braz Comput Soc 17, 3–18 (2011). https://doi.org/10.1007/s13173-010-0024-0

Download citation

Keywords

  • Sensor network
  • Weighted clustering
  • Connected dominating set
  • Load balancing
  • Mobility