An Optimized Approach to Minimize Broadcast in Communication of Self Organized Wireless Networks

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 199)

Abstract

This paper proposes the strategy for effective connections in backbone of self organized wireless networks with role based approach. Various applications like disaster management, home monitoring and office automation, shows increasing demand for wireless networks. Nodes in a wireless and ad-hoc networks are free to move. Each node plays the efficient role for formation of backbone with local interaction. In this approach four roles are identified: Agent, Leader, Willingness to act as a Gateway and Gateway. Each node is playing one of the roles and backbone reconfiguration is performed with changes in environment. ‘Willingness to act as gateway’ node avoids the problem of duplicate gateways and unnecessary broadcast. Thus forming an efficient backbone provides good resource conservation property. Number of links of MST and proposed strategy are compared for performance analysis. As compared to the MST, proposed algorithm shows near solution for network connections. This approach utilizes resources in optimized way. In case of failure of original gateway on path, other appropriate device plays the role of original gateway.

Keywords

wireless sensor network emergent behavior clustering self organization wireless devices networks wireless communication 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Shirsat, N., Game, P.: Role Based Approach for Effective Connections in Backbone of Self Organized Wireless Networks. In: Satapathy, S.C., Avadhani, P.S., Abraham, A. (eds.) Proceedings of the InConINDIA 2012. AISC, vol. 132, pp. 763–768. Springer, Heidelberg (2012)Google Scholar
  2. 2.
    Prehofer, C., Bettstetter, C.: Self organization in communication networks: Principles and design paradigms. IEEE Communication Magazine 43(7), 78–85 (2005)CrossRefGoogle Scholar
  3. 3.
    Orfanus, D., Heimfarth, T., Janacik, P.: An Approach for Systematic Design of Emergent Self-Organization in Wireless Sensor Networks. In: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns, Computation World 2009, November 15-20, pp. 92–98 (2009)Google Scholar
  4. 4.
    Kacimi, R., Dhaou, R., Beylot, A.-L.: Energy-Aware Self-Organization Algorithms for Wireless Sensor Networks. In: Global Telecommunications Conference, IEEE GLOBECOM 2008, November 30-December 4, pp. 1–5. IEEE (2008)Google Scholar
  5. 5.
    Yun, B., Song-Bo, J., Li, X.: Self-Organized Algorithm Simulation for Wireless Sensor Networks. In: 2009 Second International Symposium on Information Science and Engineering (ISISE), December 26-28, pp. 523–526 (2009)Google Scholar
  6. 6.
    Olascuaga-Cabrera, J.G., Lopez-Mellado, E., Ramos-Corchado, F.: Self-organization of mobile devices networks. In: Proc. IEEE Int. Conf. on Systems of Systems Engineering, pp. 1–6 (2009)Google Scholar
  7. 7.
    Liang, O., Ekercioglu, Y.A.S., Mani, N.: Gateway multipoint relays-an mpr-based broadcast algorithm for ad hoc networks. In: Proc.10th IEEE Singapore Int. Conf. Communication Systems (ICCS), pp. 1–6 (2006)Google Scholar
  8. 8.
    Zatout, Y., Campo, E., Llibre, J.-F.: WSN-HM: Energy-efficient Wireless Sensor Network for home monitoring. In: 2009 5th International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), December 7-10, pp. 367–372 (2009)Google Scholar
  9. 9.
    Correia, L.H., Macedo, D.F., dos Santos, A.L., Loureiro, A.A., Nogueira, J.M.S.: Transmission power control techniques for wireless sensor networks. Comput. Netw. 51(17), 4765–4779 (2007)CrossRefMATHGoogle Scholar
  10. 10.
    Funke, S., Kesselman, A., Meyer, M.S.U.: A simple improved distributed algorithm for minimum CDS in unit disk graphs. In: Proc. IEEE Int. Conf. Wireless Mobile Computing, Networking, Communications (WiMob), vol. 2, pp. 220–223 (August 2005)Google Scholar
  11. 11.
    Nieberg, T., Hurink, J.: Wireless communication graphs. In: Proc. 2004 Intelligent Sensors, Sensor Networks, Information Processing Conf., pp. 367–372 (December 2004)Google Scholar
  12. 12.
    DARPA, The network simulator -ns-2 (1989), http://www.isi.edu/nsnam/ns/

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Computer Engineering DepartmentPune Institute Of Computer TechnologyPuneIndia

Personalised recommendations