Skip to main content

Advertisement

SpringerLink
Log in

An Energy Efficient Routing Algorithm for WSNs Using Intelligent Fuzzy Rules in Precision Agriculture

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Many agricultural activities can be highly enhanced by using sensor networks and data mining techniques. One of these activities is the regulation of the quantity of water in cultivated fields. Moreover, wireless sensor network have become a more emerging technology in precision agriculture during the recent years. The important issue in the design of wireless sensor networks is the utilization of energy and to enhance the lifetime of the sensor nodes. In this paper, a new intelligent routing protocol has been proposed to improve the network lifetime and to provide energy efficiency in the routing process which is used to provide data to the irrigation system. This novel intelligent energy efficient routing protocol uses fuzzy rules and the protocol is called as Terrain based Routing using Fuzzy rules for precision agriculture. The fuzzy inference system developed in this work has been used to take decisions for routing. The system has been implemented and compared with two routing algorithms called Region Based Routing and Equalized Cluster Head Election Routing Protocol. The experimental results show that the proposed algorithm performs better than the other existing algorithms.

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
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Chaudhary, D. D., Nayse, S. P., & Waghmare, L. M. (2011). Application of wireless sensor networks for greenhouse parameter control in precision agriculture. International Journal of Wireless and Mobile Networks (IJWMN),3, 140–149.

    Article  Google Scholar 

  2. Rault, T., Bouabdallah, A., & Challal, Y. (2014). Energy efficiency in wireless sensor networks: A top-down survey. Computer Networks,67, 104–122.

    Article  Google Scholar 

  3. Logambigai, R., & Kannan, A. (2014). QEER: QoS aware energy efficient routing protocol for wireless sensor networks. In: 2014 Sixth international conference on advanced computing (ICoAC) (pp. 57–60). IEEE.

  4. Arunraja, M., Malathi, V., & Sakthivel, E. (2015). Energy conservation in WSN through multilevel data reduction scheme. Microprocessors and Microsystems,39, 348–357.

    Article  Google Scholar 

  5. Selvi, M., Logambigai, R., Ganapathy, S., Sai Ramesh, L., Khanna Nehemiah, H. & Kannan A. (2016). Fuzzy temporal approach for energy efficient routing in WSN. In: Proceedings of the international conference on informatics and analytics (pp. 1–5). ACM.

  6. Muthurajkumar, S., Ganapathy, S., Vijayalakshmi, M., & Kannan, A. (2017). An intelligent secured and energy efficient routing algorithm for MANETs. Wireless Personal Communications,96(2), 1753–1769.

    Article  Google Scholar 

  7. Heinzelman, W. R., Chandrakasan, A. & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Hawaii international conference on system sciences (pp. 1–10).

  8. Lung, C. H., & Zhou, C. (2010). Using hierarchical agglomerative clustering in wireless sensor networks: An energy-efficient and flexible approach. Ad Hoc Networks,8, 328–344.

    Article  Google Scholar 

  9. Dong, X., Vuran, M. C., & Irmak, S. (2013). Autonomous precision agriculture through integration of wireless underground sensor networks with center pivot irrigation systems. Ad Hoc Networks,11, 1975–1987.

    Article  Google Scholar 

  10. Vellidis, G., Tucker, M., Perry, C., Kvien, C., & Bednarz, C. (2008). A real-time wireless smart sensor array for scheduling irrigation. Computers and Electronics in Agriculture,61, 44–50.

    Article  Google Scholar 

  11. Sudha, M. N., Valarmathi, M. L., & Babu, A. S. (2011). Energy efficient data transmission in automatic irrigation system using wireless sensor networks. Computers and Electronics in Agriculture,78, 215–221.

    Article  Google Scholar 

  12. Goumopoulos, C., Flynn, B., & Kameas, A. (2014). Automated zone-specific irrigation with wireless sensor actuator network and adaptable decision support. Computers and Electronics in Agriculture,105, 20–33.

    Article  Google Scholar 

  13. Shah, S. K., Rane, S. J., & Vishwakarma, D. (2012). A simulation study of behaviour of wireless motes with reference to parametric variation. International Journal of Advanced Research in Electrical Electronics and Instrumentation Engineering,1, 91–95.

    Google Scholar 

  14. Dehghani, S., Pourzaferani, M., & Barekatain, B. (2015). Comparison on energy-efficient cluster based routing algorithms in wireless sensor network. Procedia Computer Science,72, 535–542.

    Article  Google Scholar 

  15. More, A., & Raisinghani, V. (2017). A survey on energy-efficient coverage protocols in wireless sensor networks. Journal of King Saud University - Computer and Information Sciences, 29(4), 428–448.

    Article  Google Scholar 

  16. Selvi, M., Velvizhy, P., Ganapathy, S., Khanna Nehemiah, H., & Kannan, A. (2017). A rule based delay constrained energy efficient routing technique for wireless sensor networks. Cluster Computing,22, 10839–10848. https://doi.org/10.1007/s10586-017-1191-y.

    Article  Google Scholar 

  17. Sabet, M., & Naji, H. (2016). An energy efficient multi-level route-aware clustering algorithm for wireless sensor networks: A self-organized approach. Computers & Electrical Engineering,56, 399–417.

    Article  Google Scholar 

  18. Zhang, W., Han, G., Feng, Y., & Lloret, J. (2017). IRPL: An energy efficient routing protocol for wireless sensor networks. Journal of Systems Architecture,75, 35–49.

    Article  Google Scholar 

  19. Mohemed, R. E., Saleh, A. I., Abdelrazzak, M., & Samra, A. S. (2017). Energy-efficient routing protocols for solving energy hole problem in wireless sensor networks. Computer Networks,114, 51–66.

    Article  Google Scholar 

  20. Thangaramya, K., Logambigai, R., SaiRamesh, L., Kulothungan, K., Kannan, A., & Ganapathy, S. (2017). An energy efficient clustering approach using spectral graph theory in wireless sensor networks. In: Second international conference on recent trends and challenges in computational models (ICRTCCM) (pp. 126–129). IEEE.

  21. Sun, X., Chen, H., Wu, X., Yin, X., & Song, W. (2016). Opportunistic communications based on distributed width-controllable braided multipath routing in wireless sensor networks. Ad Hoc Networks,36, 349–367.

    Article  Google Scholar 

  22. Kumar, V., & Kumar, S. (2016). Energy balanced position-based routing for lifetime maximization of wireless sensor networks. Ad Hoc Networks,52, 117–129.

    Article  Google Scholar 

  23. Javaid, N., Hussain, S., Ahmad, A., Imran, M., Khan, A., & Guizani, M. (2017). Region based cooperative routing in underwater wireless sensor networks. Journal of Network and Computer Applications,92, 31–41.

    Article  Google Scholar 

  24. Ganapathy, S., Sethukkarasi, R., Yogesh, P., Vijayakumar, P., & Kannan, A. (2014). An intelligent temporal pattern classification system using fuzzy temporal rules and particle swarm optimization. Sadhana,39, 283–302.

    Article  MathSciNet  Google Scholar 

  25. Singh, R., & Verma, A. K. (2017). Energy efficient cross layer based adaptive threshold routing protocol for WSN. AEU-International Journal of Electronics and Communications,72, 166–173.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Science and Technology, CEG Campus, Anna University, Chennai, 600 025, India

    V. Pandiyaraju, R. Logambigai & Arputharaj Kannan

  2. School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, 600 127, India

    Sannasi Ganapathy

Authors
  1. V. Pandiyaraju
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. R. Logambigai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sannasi Ganapathy
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Arputharaj Kannan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to V. Pandiyaraju.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pandiyaraju, V., Logambigai, R., Ganapathy, S. et al. An Energy Efficient Routing Algorithm for WSNs Using Intelligent Fuzzy Rules in Precision Agriculture. Wireless Pers Commun 112, 243–259 (2020). https://doi.org/10.1007/s11277-020-07024-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-020-07024-8

Keywords

Search

Navigation