Advertisement

Betweenness Based Self-adaptive Relay Station Selection Algorithm in Cooperative Communication

  • Xiaolong Deng
  • Yuxiao Li
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 143)

Abstract

Analysis of real communication network’s information transmission performance especially in WSN (Wireless Sensor Network) has always been the research hotpots of wireless network communication efficiency. In this article, four different node fault generation policies are adopted on network datasets including real communication networks and simulated networks to test network’s resilience. Experiments focus on the relationship between fault nodes and network structure indications .It is found that betweenness based strategy is more harmful to network structure related to network’s information transmission performance. After modifying traditional WSN relay station select algorithm, the self-adaptive relay station selection algorithm in cooperative communication based on node’s betweenness is proposed in this arcitle to promote information transmit efficiency in WSN in the time of information transmit and decrease transmit time.

Keywords

WSN Self-Adaptive Betweenness Routing Selecting Algorithm Cooperative Communication 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Subramanian, M.: Network Management principles and practices, pp. 562–563. High Education Press (2002)Google Scholar
  2. 2.
    Xu, J., Wang, X.F.: Cascading failures in scale-free coupled map lattices. Physical A 349, 685–692 (2005)CrossRefGoogle Scholar
  3. 3.
    Holme, P., Kim, B.J., Yoon, C.N., Han, S.K.: Attack vulnerability of complex networks. Physical Review E 65, 056109 (2002)CrossRefGoogle Scholar
  4. 4.
    Newman, M.E.J.: Finding community structure in networks using the eigenvectors of matrices. Phys. Rev. E 74, 036104 (2006)CrossRefGoogle Scholar
  5. 5.
    Nanavati, A.A., Singh, R., et al.: Analyzing the structure and evolution of massive telecom graphs. IEEE Transactions on Knowledge and Data Engineering 20(5), 703–718 (2008)CrossRefGoogle Scholar
  6. 6.
    Zhang, G., Zhang, G.: An Algorithm for Internet AS Graph Betweenness Centrality Based on Backtrack. Journal of Computer Research and Development 43(10), 1790–1796 (2006)CrossRefGoogle Scholar
  7. 7.
    Steinder, M., Sethib, A.S.: A survey of fault localization techniques in computer network. Science of Computer Programming 53(2), 165–194 (2004)MathSciNetzbMATHCrossRefGoogle Scholar
  8. 8.
    Albert, R., Jeong, H., Barabási, A.-L.: Error and attack tolerance of complex networks. Nature 406, 378–382 (2000)CrossRefGoogle Scholar
  9. 9.
    Newman, M.E.J., Ghoshal, G.: Bicomponents and the Robustness of Networks to Failure. Phys. Rev. Lett. 100, 138701 (2008)CrossRefGoogle Scholar
  10. 10.
    Laneman, J.N., Wornell, G.W.: Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks. IEEE Trans. Inf. Theory 49(10), 2415–2425 (2003)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Zhao, Y., Adve, R., Lim, T.J.: Improving amplify-and-forward relay networks: optimal power allocation versus selection. IEEE Trans. Wireless Commun. 6(8), 3114–3123 (2007)Google Scholar
  12. 12.
    Ikki, S.S., Ahmed, M.H.: Performance analysis of generalized selection combining for amplify-and-forward cooperative-diversity networks. In: IEEE International Conference on Communications, ICC, Dresden, Germany (June 2009)Google Scholar
  13. 13.
    Jing, Y., Jafarkhani, H.: Single and Multiple Relay Selection Schemes and their Diversity Orders. IEEE Trans. Wireless Commun., 1414–1423 (March 2009)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Beijing University of Posts and TelecommunicationsBeijingChina

Personalised recommendations