Advertisement

An Approach to Construct Weighted Minimum Spanning Tree in Wireless Sensor Networks

  • Soumya SahaEmail author
  • Lifford McLauchlan
Part of the Studies in Computational Intelligence book series (SCI, volume 569)

Abstract

Topology control is critical to extend the lifetime of energy constrained Wireless Sensor Networks (WSNs). Topology control mechanism can be divided into two processes: topology construction and topology maintenance. During topology construction one creates a reduced topology to ensure network connectivity and coverage. In topology maintenance, one recreates or changes the reduced topology when the network is no longer optimal. In this research the authors concentrate on Minimum Spanning Tree (MST) which is a commonly seen problem during the design of a topology construction protocol for WSNs. As the amount of running time and messages successfully delivered are important metrics to measure the efficacy of distributed algorithms, much research to create simple, local and energy efficient algorithms for WSNs thereby creating sub optimal MSTs has been studied. In this research, two popular approaches are discussed to create a Spanning Tree in the WSNs- Random Nearest Neighbor Tree (Random NNT) and Euclidian Minimum Spanning Tree (Euclidian MST). Next, the authors propose a method which has the goals to balance the network load evenly among all of the nodes and increase the number of successful message deliveries to the sink. Finally a comparison between the three algorithms is conducted in the Matlab environment. Simulation results demonstrate significant improvement for both load balancing and number of message deliveries after implementation of the proposed algorithm.

Keywords

Topology construction protocol Minimum Spanning Tree Nearest Neighbor Tree Load balancing Simple Weighted Spanning Tree 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Khan, M., Pandurangan, G.: Distributed Algorithms for Constructing Approximate Minimum Spanning Trees in Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems 20(1), 124–139 (2009)CrossRefGoogle Scholar
  2. 2.
    Cohen, L., Avrahami-Bakish, G., et al.: Real-time data mining of non-stationary data streams from sensor networks. Information Fusion 9(3), 344–353 (2008)CrossRefGoogle Scholar
  3. 3.
    Wang, X., Ma, J., Wang, S., Bi, D.: Time Series Forecasting Energy-efficient Organization of Wireless Sensor Networks. IEEE Sensors Journal 7(1), 1766–1792 (2007)CrossRefGoogle Scholar
  4. 4.
    Kui, X., Sheng, Y., Du, H., Liang, J.: Constructing a CDS-Based Network Backbone for Data Collection in Wireless Sensor Networks. International Journal of Distributed Sensor Networks 2013, Article ID 258081, 12 (2013), http://dx.doi.org/10.1155/2013/258081
  5. 5.
    Mario, P., Rojas, W.: Topology control in wireless sensor networks. PhD Dissertation, University of South Florida (2010)Google Scholar
  6. 6.
    Raei, H., Sarram, M., Adibniya, F., Tashtarian, F.: Optimal distributed algorithm for minimum connected dominating sets in Wireless Sensor Networks. In: IEEE Conference on Mobile Ad Hoc and Sensor Systems, pp. 695–700 (2008)Google Scholar
  7. 7.
    Butenko, S., Cheng, X., Oliveira, C., Pardalos, P.M.: A New Heuristic for the Minimum Connected Dominating Set Problem on Ad Hoc Wireless Networks, pp. 61–73. Kluwer Academic (2004)Google Scholar
  8. 8.
    Chen, B., Jamieson, K., Balakrishnan, H., Morris, R.: Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. Wireless Networks 8(5), 481–494 (2002)CrossRefzbMATHGoogle Scholar
  9. 9.
    Guha, S., Khuller, S.: Approximation algorithms for connected dominating sets. Algorithmica 20(4), 374–387 (1998)CrossRefzbMATHMathSciNetGoogle Scholar
  10. 10.
    Kumar, V., Arunan, T., Balakrishnan, N.: E-span: Enhanced-span with directional antenna. In: Proceedings of IEEE Conference on Convergent Technologies for Asia-Pacific Region, vol. 2, pp. 675–679 (2002)Google Scholar
  11. 11.
    Wu, J., Cardei, M., Dai, F., Yang, S.: Extended dominating set and its applications in ad hoc networks using cooperative communication. IEEE Trans. on Parallel and Distributed Systems 17(8), 851–864 (2006)CrossRefGoogle Scholar
  12. 12.
    Wu, J., Dai, F.: An extended localized algorithm for connected dominating set formation in ad hoc wireless networks. IEEE Transactions on Parallel and Distributed Systems 15(10), 908–920 (2004)CrossRefGoogle Scholar
  13. 13.
    Wu, J., Li, H.: On calculating connected dominating set for efficient routing in ad hoc wireless networks. In: Proceedings of the 3rd ACM International Workshop on Discrete Algorithms and Methods for Mobile Computing and Communications, pp. 7–14 (1999)Google Scholar
  14. 14.
    Yuanyuan, Z., Jia, X., Yanxiang, H.: Energy efficient distributed connected dominating sets construction in wireless sensor networks. In: Proceeding of the 2006 ACM International Conference on Communications and Mobile Computing, pp. 797–802 (2006)Google Scholar
  15. 15.
    Wightman, P., Labrador, M.: A3: A topology control algorithm for wireless sensor networks. In: Proceedings of IEEE Globecom (2008)Google Scholar
  16. 16.
    Khan, M.A.M.: Distributed Approximation Algorithms for Minimum Spanning Trees and other Related Problems with Applications to Wireless Ad Hoc Networks. Ph.D. Dissertation, Purdue University (December 2007)Google Scholar
  17. 17.
    Saha, S.: Topology Control Protocols in Wireless Sensor Networks. MS Thesis, Texas A&M University-Kingsville (May 2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Electrical Engineering and Computer ScienceTexas A&M UniversityKingsvilleUSA

Personalised recommendations