Routing algorithm of energy efficient wireless sensor network based on partial energy level

  • Yaning Wang
  • Zhaofeng Wang


In order to improve the power supply problem of network nodes, the energy efficient routing algorithm of wireless sensor network is studied and improved. A new energy efficient routing algorithm and protocol is proposed to prolong the lifetime of the network. First, the energy efficient (3PEC-MBCR) routing algorithm based on partial energy level is proposed in this paper. Secondly, according to the PEC-AODV routing protocol, the energy consumption of the network and the balance of energy consumption of each node are taken into account, so as to prolong the network lifetime. Finally, the PEC-AODV protocol module is added to the NS-2 simulation platform, and the simulation and performance evaluation of the PEC-AODV protocol are made by NS-2. The simulation results show that the algorithm not only reduces the total energy consumption of the network, but also balances the energy consumption between nodes, which maximizes the lifetime of each node. It is concluded that the PEC-AODV routing protocol is more effective in energy utilization than the existing AODV routing protocol or other energy-efficient routing protocols, which results in a certain role in prolonging the lifetime of the entire network.


Wireless sensor network ZigBee Energy efficient routing protocol Network survival time 



The authors acknowledge the Fundamental Research Funds for the Central Universities (No. 2015MS99).


  1. 1.
    Sabet, M., Naji, H.: An energy efficient multi-level route-aware clustering algorithm for wireless sensor networks: a self-organized approach. Comput. Electr. Eng. 56(C), 399–417 (2016)CrossRefGoogle Scholar
  2. 2.
    Zeng, B., Dong, Y.: An improved harmony search based energy-efficient routing algorithm for wireless sensor networks. Appl. Soft Comput. 41(C), 135–147 (2016)CrossRefGoogle Scholar
  3. 3.
    Jayekumar, M., Nagarajan, V.: A novel energy-link failure recovery routing (E-LFRR) algorithm for QOS optimization in wireless sensor network. Int. Res. J. Electron. Comput. Eng. 2(4), 17–21 (2016)Google Scholar
  4. 4.
    Dien, M.E.E., Youssif, A.A.A., Ghalwash, A.Z.: A framework for qos-aware execution of workflows over the cloud. Wirel. Sens. Netw. 08(3), 25–36 (2015)CrossRefGoogle Scholar
  5. 5.
    Yu, J., Zhang, X.: A cross-layer wireless sensor network energy-efficient communication protocol for real-time monitoring of the long-distance electric transmission lines. J. Sens. 2015(5), 1–13 (2015)Google Scholar
  6. 6.
    Kariman-Khorasani, M., Pourmina, M.A.: Maximum lifetime routing problem in asynchronous duty-cycled wireless sensor networks. Wirel. Netw. 21(8), 2501–2517 (2015)CrossRefGoogle Scholar
  7. 7.
    Omar, M., Yahiaoui, S., Bouabdallah, A.: Reliable and energy aware query-driven routing protocol for wireless sensor networks. Ann. Telecommun. 71(1–2), 73–85 (2016)CrossRefGoogle Scholar
  8. 8.
    Zheng, J.Y., Ko, R.S.: Distributed de la garza algorithm for load-balancing routing in wireless sensor networks. Wirel. Netw. 21(1), 297–314 (2015)CrossRefGoogle Scholar
  9. 9.
    Jin, Y., Ding, Y., Hao, K., Jin, Y.: An endocrine-based intelligent distributed cooperative algorithm for target tracking in wireless sensor networks. Soft. Comput. 19(5), 1427–1441 (2015)CrossRefGoogle Scholar
  10. 10.
    Rodríguez-Pérez, M., Herrer A-Alonso, S., Ndez-Veiga, M., et al.: An ant colonization routing algorithm to minimize network power consumption. J. Netw. Comput. Appl. 58(C), 217–226 (2015)CrossRefGoogle Scholar
  11. 11.
    Wang, C., Li, J., Yang, Y., Ye, F.: Combining solar energy harvesting with wireless charging for hybrid wireless sensor networks. IEEE Trans. Mob. Comput. 99, 1 (2017)Google Scholar
  12. 12.
    Tang, D., Li, T., Ren, J., Wu, J.: Cost-aware secure routing (caser) protocol design for wireless sensor networks. IEEE Trans. Parallel Distrib. Syst. 26(4), 960–973 (2015)CrossRefGoogle Scholar
  13. 13.
    Hao, K., Jin, Z., Shen, H., Wang, Y.: An efficient and reliable geographic routing protocol based on partial network coding for underwater sensor networks. Sensors 15(6), 12720–12735 (2015)CrossRefGoogle Scholar
  14. 14.
    Sun, Z., Yang, S., Xing, X.: A novel energy efficient multi-target associated coverage control in wireless sensor network. Open Autom. Control Syst. J. 7(1), 884–892 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Electrical and Electronic EngineeringNorth China Electric Power UniversityBaodingChina
  2. 2.School of ArtAgricultural University of HebeiBaodingChina

Personalised recommendations