Skip to main content

Advertisement

Log in

Improve Performance of Wireless Sensor Network Clustering Using Mobile Relay

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Wireless sensor networks sense events, collect data and forward it to the infrastructural node, called sink, for further processing and assessment. The communication from sensor node to the sink is an energy consuming task. Clustering is one of the strategies to provide communication in the sensor network. Maintenance of the clusters and re-clustering are important to improve connectivity of the network. An efficient clustering protocol reduces the energy consumption in addition to providing connectivity and communication path, because energy is a scarce commodity in wireless sensor network. The following paper proposes a clustering procedure to reduce energy consumption, reduce delay in communication and improve the connectivity of the network. The proposed algorithm aims to improve the performance and lifetime of the network by improving the above mentioned parameters.

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

Access this article

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
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Heinzelman W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd annual Hawaii International conference on system sciences, 2000. IEEE.

  2. Wang, R., Liu, G., & Zheng, C. (2007). A clustering algorithm based on virtual area partition for heterogeneous wireless sensor networks. In International conference on mechatronics and automation, 2007. ICMA 2007. IEEE.

  3. Gou, H., Yoo, Y., & Zeng, H. (2009). A partition-based LEACH algorithm for wireless sensor networks. In Ninth IEEE international conference on computer and information technology, 2009. CIT’09 (Vol. 2). IEEE.

  4. Ma, D., et al. (2013). A virtual area partition clustering protocol with assistant cluster heads for wireless sensor networks. In 2013 10th IEEE international conference on control and automation (ICCA). IEEE.

  5. Muni, V. K., Kandasamy, A., & Chandrasekaran, K. (2013). Energy-efficient edge-based network partitioning scheme for wireless sensor networks. In 2013 international conference on advances in computing, communications and informatics (ICACCI). IEEE.

  6. Lin, H., Chen, P., & Wang, L. (2014). Fan-shaped clustering for large-scale sensor networks. In 2014 international conference on cyber-enabled distributed computing and knowledge discovery (CyberC). IEEE.

  7. Lin, Hai, Wang, Lusheng, & Kong, Ruoshan. (2015). Energy efficient clustering protocol for large-scale sensor networks. IEEE Sensors Journal,15(12), 7150–7160.

    Article  Google Scholar 

  8. Tripathi, R. K., Singh, Y. N., & Verma, N. K. (2013). Clustering algorithm for non-uniformly distributed nodes in wireless sensor network. Electronics Letters,49(4), 299–300.

    Article  Google Scholar 

  9. Liao, Ying, Qi, Huan, & Li, Weiqun. (2013). Load-balanced clustering algorithm with distributed self-organization for wireless sensor networks. IEEE Sensors Journal,13(5), 1498–1506.

    Article  Google Scholar 

  10. Izadi, Davood, Abawajy, Jemal, & Ghanavati, Sara. (2015). An alternative clustering scheme in WSN. IEEE Sensors Journal,15(7), 4148–4155.

    Article  Google Scholar 

  11. Zhang, Y., & Zhou, R. (2017). Networks energy-efficient clustering algorithm based on fuzzy inference system. In 2017 29th Chinese control and decision conference (CCDC). IEEE.

  12. Thakkar, Ankit, & Kotecha, Ketan. (2014). Cluster head election for energy and delay constraint applications of wireless sensor network. IEEE Sensors Journal,14(8), 2658–2664.

    Article  Google Scholar 

  13. Ansari, N., & Paul R. K. (2014) Modified Leach in wireless sensor network. IOSR Journal of Computer Engineering, 16(6), 71–78.

    Article  Google Scholar 

  14. Benaouda, N., & Mostefai, M. (2015). A new two-level clustering scheme for partitioning in distributed wireless sensor networks. International Journal of Distributed Sensor Networks, 11(5), 1–13.

    Article  Google Scholar 

  15. Siavoshi, Saman, Kavian, Yousef S., & Sharif, Hamid. (2016). Load-balanced energy efficient clustering protocol for wireless sensor networks. IET Wireless Sensor Systems,6(3), 67–73.

    Article  Google Scholar 

  16. Jia, D., et al. (2016). Dynamic cluster head selection method for wireless sensor network. IEEE Sensors Journal,16(8), 2746–2754.

    Article  Google Scholar 

  17. Pal, V., Singh, G., & Yadav, R. P. (2015). Balanced cluster size solution to extend lifetime of wireless sensor networks. IEEE Internet of Things Journal,2(5), 399–401.

    Article  Google Scholar 

  18. Leu, J.-S., et al. (2015). Energy efficient clustering scheme for prolonging the lifetime of wireless sensor network with isolated nodes. IEEE Communications Letters,19(2), 259–262.

    Article  MathSciNet  Google Scholar 

  19. Lv, C., & Qiao, L. (2016). Evenly-distributed clustering for wireless sensor network: A scalable, energy-efficient approach. In IEEE international conference of online analysis and computing science (ICOACS). IEEE.

  20. Prasath, K. A., & Shankar, T. (2015). RMCHS: Ridge method based cluster head selection for energy efficient clustering hierarchy protocol in WSN. In 2015 international conference on smart technologies and management for computing, communication, controls, energy and materials (ICSTM). IEEE.

  21. Zhou, Yuan, Wang, Ning, & Xiang, Wei. (2017). Clustering hierarchy protocol in wireless sensor networks using an improved PSO algorithm. IEEE Access,5, 2241–2253.

    Article  Google Scholar 

  22. Mondal, S., Ghosh, S., & Biswas, U. (2016). ACOHC: Ant colony optimization based hierarchical clustering in wireless sensor network. In International conference on emerging technological trends (ICETT). IEEE.

  23. RejinaParvin, J., & Vasanthanayaki, C. (2015). Particle swarm optimization-based clustering by preventing residual nodes in wireless sensor networks. IEEE Sensors Journal,15(8), 4264–4274.

    Article  Google Scholar 

  24. Gupta, N., et al. (2017). Clustering in WSN: Techniques and future challenges. In 2017 4th international conference on computing, communication, control and automation (ICCUBEA). IEEE.

  25. Gupta, N., et al. (2017). Benchmarks for evaluation of wireless sensor network clustering. In 2017 2nd Springer CCIS smart trends for information technology and computer communications (SmartCom).

  26. NS2. https://www.isi.edu/nsnam/ns/.

  27. Royer, E. M., & Perkins, C. E. (1999). Multicast operation of the ad-hoc on-demand distance vector routing protocol. In Proceedings of the 5th annual ACM/IEEE international conference on mobile computing and networking. ACM.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nishi Gupta.

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

Gupta, N., Pawar, P.M. & Jain, S. Improve Performance of Wireless Sensor Network Clustering Using Mobile Relay. Wireless Pers Commun 110, 983–998 (2020). https://doi.org/10.1007/s11277-019-06769-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-019-06769-1

Keywords

Navigation