Skip to main content
Log in

GCCR: An Efficient Grid Based Clustering and Combinational Routing in Wireless Sensor Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

A novel algorithm for clustering and routing is proposed based on grid structure in wireless sensor networks. According to the size of the area and transmission range, a suitable grid size is calculated and a virtual grid structure is constructed. A cluster head is selected in each grid based on the nearest distance to the midpoint of grid. A localized single path strategy is followed in order to forward data within a grid. To forward aggregate data from cluster head to the Sink, angular inclination based combinational routing model is implemented. The simulation results show that the algorithm performs better in terms of improving the network lifetime and scalability compared to recent and relevant existing algorithms.

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.

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. Farouk, F., Rizk, R., & Zaki, FW. (2014). Multi-level stable and energy-efficient clustering protocol in heterogeneous wireless sensor networks. IET Wireless Sensor Systems, 4(4), 159–169.

    Article  Google Scholar 

  2. Liu, X. (2015). A typical hierarchical routing protocols for wireless sensor networks: A review. IEEE Sensors Journal, 15(10), 5372–5383.

    Article  Google Scholar 

  3. Villas, L., Boukerche, A., et al. (2010). Highly dynamic routing protocol for data aggregation in sensor networks. Proceedings of the The IEEE symposium on Computers and Communications, 43(5), 1–5.

    Google Scholar 

  4. Mini, S., Udgata, Siba K., & Sabat, Samrat L. (2014). Sensor deployment and scheduling for target coverage problem in wireless sensor network. IEEE Sensors Journal, 14(3), 636–644.

    Article  Google Scholar 

  5. Al-Jemeli, M., & Hussin, F. A. (2015). An energy efficient cross-layer network operation model for IEEE 802.15.4-based mobile wireless sensor networks. IEEE Sensors Journal, 15(2), 684–692.

    Article  Google Scholar 

  6. Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660–670.

    Article  Google Scholar 

  7. Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions On Mobile Computing, 3(4), 366–379.

    Article  Google Scholar 

  8. Chen, Y.-C., & Wen, C.-Y. (2013). Distributed clustering with directional antennas for wireless sensor networks. IEEE Sensors Journal, 13(6), 2166–2180.

    Article  Google Scholar 

  9. Guiloufi, Awatef Ben Fradj, Nasri, Nejah, & Kachouri, Abdennaceur. (2016). An energy-efficient unequal clustering algorithm using ‘Sierpinski Triangle’ for WSNs. Wireless Personal Communications, 88, 449–465.

    Article  Google Scholar 

  10. Xu, Y., Heidemann, J., & Estrin, D. (2001). Geography-informed energy conservation for ad hoc routing. In Proceedings of ACM/IEEE international conference on mobile computing and networking (MOBICOM) (pp. 70–84).

  11. Chen, B., Jamieson, K., Balakrishnan, H., & Morris, R. (2002). Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. ACM Wireless Networks, 8(5), 481–494.

    Article  MATH  Google Scholar 

  12. Li, H., Shunjie, X., Guoqiang, W., Zhe, J. (2009). Uneven virtual grid-based clustering routing protocol for wireless sensor networks. In Proceeding of IEEE international conference on information and automation, China (pp. 397–402).

  13. Kawadia, V., & Kumar, P. R. (2003). Power control and clustering in ad hoc networks. In Proceedings of the EEE INFOCOM conference (pp. 459–469).

  14. Liu, W-D. et al. (2010). A low power grid-based cluster routing algorithm of wireless sensor networks. In International forum on information technology and applications (pp. 227–229).

  15. Jannu, S., & Jana, P. K. (2014). Energy efficient grid based clustering and routing algorithms for wireless sensor networks. In International conference on communication systems and network technologies (pp. 63–68).

  16. Yan, B., Zhou, X., Wang, H., & Li, B. (2007). A grid-based clustering method for large-scale wireless sensor networks. In IEEE International conference proceedings (pp. 414–418).

  17. Lou, C., & Zhuang, W. (2016). Energy-efficient routing over coordinated sleep scheduling in wireless ad hoc networks. Peer-to-Peer Networking and Applications, 9, 384–396.

    Article  Google Scholar 

  18. Aswatha K. M. et al. (2013). Energy efficient clustering and grid based routing in wireless sensor networks. In Proceeings of ICAdC, AISC (Vol. 174, pp. 69–74).

  19. Ananth Rao et al. (2003). Geographic routing without location information. In Proceedings of 9th ACM Mobile Computing and Networking (MobiCom) (pp. 96–108).

  20. Ye, F., Luo, H. Y., Cheng, J. (2002). A two-tier data dissemination model for larger-scale wireless sensor networks. In Proceedings for the 8th annual international conference on mobile computing and networking (pp. 148–159). Atlanta: ACM.

  21. Soni, V., & Mallick, D. K. (2015). A novel scheme to minimize hop count for GAF in wireless sensor networks: Two-level GAF. Journal of Computer Networks and Communications, 1–10.

  22. Leong, B. W. L. (2006). New techniques for geographic routing. Thesis, Massachusetts Institute of Technology.

  23. Xu, Y., Heide, J., & Estrin, D. (2001). Geography-informed energy conservation for ad hoc routing. In Proceedings of the 7th annual international conference on mobile computing and networking (pp. 70–84). Rome: ACM

  24. Ko, Y.-B., & Vaidya, N. (2000). Location-aided routing (LAR) in mobile ad hoc networks. Wireless Networks, 6(4), 307–321.

    Article  MATH  Google Scholar 

  25. Gao, Q., Blow, K. J., Holding, D. J., Marshall, I. W., & Peng, X. H. (2006). Radio Range adjustment for energy efficient wireless sensor networks. Adhoc Networks, 4(1), 75–82.

    Article  Google Scholar 

  26. Zhu, J. (2009). On the power efficiency and optimal transmission range of wireless sensor nodes. In IEEE Conference (pp. 277–281).

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. Lalitha.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lalitha, K., Thangarajan, R., Udgata, S.K. et al. GCCR: An Efficient Grid Based Clustering and Combinational Routing in Wireless Sensor Networks. Wireless Pers Commun 97, 1075–1095 (2017). https://doi.org/10.1007/s11277-017-4554-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-017-4554-z

Keywords

Navigation