Advertisement

Research on Optimization Method of LEACH Routing Protocol

  • Fan Chao
  • Zhiqin HeEmail author
  • Xiumin Hu
  • Hongbo Zhou
  • Aiping Pang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 582)

Abstract

In view of the problem of cluster head selection in traditional LEACH protocol, this paper considers the residual energy of node, distance from base station, density of surrounding node and so on, and puts forward the method of selecting cluster head by secondary competition law. Then, a simple optimization of intra-cluster communication is made, and the improved I-Leach algorithm is obtained. Through MATLAB simulation it is verified that the improved algorithm can effectively improve the network life cycle.

Keywords

Secondary competition law Wireless sensor network Network life cycle I-LEACH 

Notes

Acknowledgements

Fund projects: The National Natural Science Fund 61640014; Science and Technology Plan Project of Guizhou province [2016]2302.

References

  1. 1.
    Heinzelman, W., Chandrakasan, A., Balakr Ishnan, H.: Energy efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Hawaii International Conference on System Sciences, pp. 3005–3014 (2000)Google Scholar
  2. 2.
    Karaki, J.N., Kamal, A.E.: Routing techniques in wireless sensor networks: a survey. IEEE Wirel. Commun. 11(6), 6–28 (2004)CrossRefGoogle Scholar
  3. 3.
    Anastasi, G., Conti, M., Francesco, M.D., et al.: Energy conservation in wireless sensor networks: a survey. Ad Hoc Netw. 7(3), 537–568 (2009)CrossRefGoogle Scholar
  4. 4.
    Hosseinirada, S.M., Ali Mohammadib, M., Basua, S.K., Pouyanb, A.A.: LEACH routing algorithm optimization through imperialist approach. IJE Trans. A: Basics 27(1) (January 2014)Google Scholar
  5. 5.
    Aslam, J., Li, Q., Rus, D.: Three power-aware routing algorithms for sensor networks. Wireless Commun. Mob. Comput. 3(2), 187–208 (2003)CrossRefGoogle Scholar
  6. 6.
    Zhao, M., Yang, Y., Wang, C.: Mobile data gathering with load balanced clustering and dual data uploading in wireless sensor networks. IEEE Trans. Mobile Comput. 14(4), 770–785 (2015)CrossRefGoogle Scholar
  7. 7.
    Qiao, Y., Li, X.Y., Zhao, T.: Analysis of typical military application of small satellite technology. Foreign Electron. Meas. Technol. 36(3), 47–50 (2017)Google Scholar
  8. 8.
    Zhu, Y.H., Ding, E.N.J., Hu, Y.J.: PSO optimization energy balanced routing algorithm of WSNs. Chin. J. Sci. Instrum. 36(1), 78–86 (2015)Google Scholar
  9. 9.
    Fu, H.-L., Chen, H.-C., Lin, P.: Aps: distributed air pollution sensing system on wireless sensor and robot networks. Comput. Commun. 35(9), 1141–1150 (2012)CrossRefGoogle Scholar
  10. 10.
    Elhoseny, M., Yuan, X., Yu, Z., et al.: Balancing energy consumption in heterogeneous wireless sensor networks using genetic algorithm. IEEE Commun. Lett. 19(12), 2194–2197 (2015)CrossRefGoogle Scholar
  11. 11.
    Wu, L., Du, J., Nie, L., et al.: Cluster head selection method using dynamic k value for wireless sensor network. J. Huazhong Univ. Sci. Technol. (Natural Science Edition) 43(10), 37–41 (2015)Google Scholar
  12. 12.
    Huang, T., Yi, K., Gui, G., et al.: Hierarchical routing protocol based on non-uniform clustering for wireless sensor network. J. Comput. Appl. 36(1), 66–71 (2016)Google Scholar
  13. 13.
    Li, A., Chen, G.: An improved clustering routing algorithm for energy heterogeneous wireless sensor networks. Chin. J. Sens. Actuators 30(11), 1712–1718 (2017)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Fan Chao
    • 1
  • Zhiqin He
    • 1
    Email author
  • Xiumin Hu
    • 1
  • Hongbo Zhou
    • 1
  • Aiping Pang
    • 1
  1. 1.School of Electrical EngineeringGuizhou UniversityGuiyangChina

Personalised recommendations