Skip to main content

Advertisement

SpringerLink
Log in

Energy-Balanced Strategy for Wireless Sensor Networks by Utilizing Complex Networks Synchronization Theory

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The network lifetime is limited by key nodes in wireless sensor networks (WSNs). These nodes around the base station undertake a heavy load and die earlier than the others, so an energy hole emerges. In this study, an energy-balanced strategy that contributes to redistributing energy consumption of the network is proposed for WSNs through the innovative use of complex networks synchronization theory. The betweenness centrality in complex networks is used to measure the importance of the node in the network. Constructing energy consumption synchronization functions and decreasing the maximum betweenness of the node in this study improves the synchronization capacity of energy consumption and weakens the effect of key nodes on the performance of the network, the effect of key edges is also investigated in this study. Experiment results show that compared with other algorithms, the proposed strategy delays the appearance of the first death node, therefore prolongs the lifetime of the network effectively and helps achieve balance in the energy consumption of nodes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Ramesh, M. V. (2014). Design, development, and deployment of a wireless sensor network for detection of landslides. Ad Hoc Networks, 13(SI), 2–18.

    Article  Google Scholar 

  2. Emanuele, I., Giovanni, G., Francesco, M., et al. (2012). Design and implementation of a landslide early warning system. Engineering Geology, 147(2012), 124–136.

    Google Scholar 

  3. Zulkifli, C. Z., Hassan, H. N., Ismail, W., et al. (2015). Embedded RFID and wireless mesh sensor network materializing automated production line monitoring. Acta Physica Polonica A, 128(2B), B86–B89.

    Article  Google Scholar 

  4. Jaguey, J. G., Villa-Medina, J. F., Lopez-Guzman, A., et al. (2015). Smartphone Irrigation Sensor. IEEE Sensors Journal, 15(9), 5122–5127.

    Article  Google Scholar 

  5. Unluturk, M. S., & Kaan, K. (2012). Integration of RFID and web service for assisted living. Journal of Medical Systems., 36(4), 2371–2377.

    Article  Google Scholar 

  6. Zhang, Z., Udyant, K., & Michael, N., et al. (2011). Design of an unobtrusive wireless sensor network for nighttime falls detection, In IEEE engineering in medicine and biology society conference proceedings (pp 5275–5278).

  7. Li, J., & Mohapatra, P. (2005). An analytical model for the energy hole problem in many-to-one sensor networks. In IEEE VTS vehicular technology conference proceedings (pp. 2721–2725).

  8. Nishikawa, T., Motter, A. E., Lai, Y. C., & Hoppensteadt, F. C. (2003). Heterogeneity in oscillator networks: are smaller worlds easier to synchronize? Physical Review Letters, 91(1), 014101.

    Article  Google Scholar 

  9. Hong, H., Kim, B. J., Choi, M. Y., & Park, H. (2004). Factors that predict better synchronizability on complex networks. Physical Review E, 69(6), 067105.

    Article  Google Scholar 

  10. Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of small-world networks. Nature, 393(6684), 440–442.

    Article  Google Scholar 

  11. Helmy, A. (2003). Small Worlds in wireless networks. IEEE Communications Letters, 7(10), 490–492.

    Article  Google Scholar 

  12. Zheng, G., & Liu, Q. (2010). Overview of small world network model in wireless sensor networks. Journal of Computational Information Systems, 6(10), 3471–3479.

    Google Scholar 

  13. Hawick, K. A., & James, H. A. (2003). Small-world effects in wireless agent networks. In Technical report CSTN-001 (pp. 155–164).

  14. Meng, A., & Chen, P. (2008). Construction to heterogeneous sensor networks based on effect of small world. Computer & Digital Engineering, 36(9), 98–100.

    Google Scholar 

  15. Liu, M. (2007). Approach to construction of wireless sensor networks with small world effect. Electronic Measurement Technology, 30(4), 37–40.

    Google Scholar 

  16. Matthias, R. (2007). Small worlds: Strong clustering in wireless networks. Networking and Internet Architecture, 6(3), 1–10.

    Google Scholar 

  17. Zhang, X. (2009). Model design of wireless sensor network based on scale-free network theory. In 5th international conference on wireless communications, networking and mobile computing, WiCOM (pp. 1–4).

  18. Zhu, H., Luo, H., Peng, H., Li, L., & Luo, Q. (2009). Complex networks-based energy-efficient evolution model for wireless sensor networks. Chaos, Solitons and Fractals, 41, 1828–1835.

    Article  Google Scholar 

  19. Parth, H., & Rudra Dutta, P. (2012). Centrality-based power control for hot-spot mitigation in multi-hop wireless networks. Computer Communications, 35, 1074–1085.

    Article  Google Scholar 

  20. Cuzzocrea, A., Papadimitriou, A., Katsaros, D., et al. (2012). Edge betweenness centrality: A novel algorithm for QoS-based topology control over wireless sensor networks. Journal of Network and Computer Applications, 35(2012), 1210–1217.

    Article  Google Scholar 

  21. Zhang, D., Li, G., Zheng, K., Ming, X., & Pan, Z.-H. (2014). An energy-balanced routing method based on forward-aware factor for wireless sensor networks. IEEE Transactions on Industrial Informatics, 10(1), 766–773.

    Article  Google Scholar 

  22. Chen, G., Li, C., Ye, M., & Jie, W. (2009). An unequal cluster-based routing protocol in wireless sensor networks. Wireless Networks, 15, 193–207.

    Article  Google Scholar 

  23. Zhao, H., Guo, S., Wang, X., et al. (2015). Energy-efficient topology control algorithm for maximizing networklifetime in wireless sensor networks with mobile sink. Applied Soft Computing, 34, 539–550.

    Article  Google Scholar 

  24. Tunca, C., Isik, S., Donmez, M. Y., et al. (2015). Ring routing: An energy-efficient routing protocol for wireless sensor networks with a mobile sink. IEEE Transactions on Mobile Computing, 14(9), 1947–1960.

    Article  Google Scholar 

  25. Liu, T., Li, Q., & Liang, P. (2012). An energy-balancing clustering approach for gradient-based routing in wireless sensor networks. Computer Communications, 35, 2150–2161.

    Article  Google Scholar 

  26. Abd, M. A., Majed Al-Rubeaai, S. F., Singh, B. K., et al. (2015). Extending wireless sensor network lifetime with global energy balance. IEEE Sensors Journal, 15(9), 5053–5063.

    Article  Google Scholar 

  27. Zhang, J., Liu, Y., & Li, B., et al. (2015). Achieving energy-balance with unequal clustering under single-hop transmission in wireless sensor networks. In The 14th international conference on wireless networks, ICWN’15 (pp. 146–152).

  28. Chen, L., Mao, Y., Chen, D., et al. (2007). Topology control of wireless sensor networks under an average degree constraint. Chinese Journal of computer, 30(9), 1544–1550.

    MathSciNet  Google Scholar 

  29. Heinzelman, W. B. (2000). Application-specific protocol architectures for wireless networks. PhD thesis, Massachusetts Institute of Technology.

Download references

Acknowledgements

The authors express sincere appreciation to the editors and the anonymous reviewers for their helpful comments.

Funding was provided by People’s Government of Jilin Province (Grant No. 20140204063GX).

Author information

Authors and Affiliations

  1. College of Computer Science and Technology, Chang Chun University of Science and Technology, Changchun, 130022, China

    Jing Zhang, Xin Feng & Zhuang Liu

Authors
  1. Jing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xin Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhuang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jing Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, J., Feng, X. & Liu, Z. Energy-Balanced Strategy for Wireless Sensor Networks by Utilizing Complex Networks Synchronization Theory. Wireless Pers Commun 97, 4145–4159 (2017). https://doi.org/10.1007/s11277-017-4717-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-017-4717-y

Keywords

Search

Navigation