Skip to main content

Advertisement

Log in

A geodesic distance-based routing scheme for sensor networks with irregular terrain structure

  • Original Paper
  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

The efficiency of the routing strategy is essential for the sensor-based applications at the edge of internet of things. In many practical monitoring applications, many sensor networks with irregular terrain structure are ubiquitous in nature. The forwarding candidates selected by the Euclidean distance in the routing are not appropriate. To address the problem, a Geodesic Distance-based Routing (GDDR) scheme with insurance of reliable data transmission for sensor networks with irregular terrain structure is proposed. In the GDDR scheme, a novel method is proposed firstly to calculate the geodesic distance using sampling and flooding to reduce the time complexity. In the data transmission process, the geodesic distance is applied in the selection of forwarding candidates to ensure the correct transfer direction, path connectivity and avoidance of routing holes. A certain number of forwarding candidates are selected based on the remaining energy and geodesic distance. And, the number of selected candidates is variable according to the geodesic distance to reduce and balance the energy cost. The proposed scheme not only can be used in the network with irregular topology but it also can be applied in the network with a regular shape. The performance is tested and the effectiveness of the proposed GDDR scheme is evaluated by the simulation.

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 a
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. Liang, J., Liu, W., Xiong, N., Liu, A., & Zhang, S. (2022). An intelligent and trust UAV-assisted code dissemination 5G system for industrial internet-of-things. IEEE Transactions on Industrial Informatics, 18(4), 2877–2889. https://doi.org/10.1109/TII.2021.3110734

    Article  Google Scholar 

  2. Liu, L., Chen, B., & Ma, H. (2020). SDCN: Sensory data-centric networking for building the sensing layer of IoT. ACM Transactions on Sensor Networks, 17(1), 1–25. https://doi.org/10.1145/3402452

    Article  Google Scholar 

  3. Yarinezhad, R., & Sabaei, M. (2021). An optimal cluster-based routing algorithm for lifetime maximization of internet of things. Journal of Parallel and Distributed Computing, 156, 7–24. https://doi.org/10.1016/j.jpdc.2021.05.005

    Article  Google Scholar 

  4. Rajanikanth, P., & Reddy, K. S. (2022). An efficient routing mechanism for node localization, cluster based approach and data aggregation to extend WSN lifetime. International Journal of Intelligent Engineering and Systems. https://doi.org/10.22266/ijies2022.0228.28

    Article  Google Scholar 

  5. Mohapatra, S., Mohanty, P., & Ratha, B. K. (2020). Energy efficient and multicast based greedy routing for proactive and reactive routing protocols. Advances in Data Science and Management, 37, 479–487. https://doi.org/10.1007/978-981-15-0978-0_47

    Article  Google Scholar 

  6. Li, L., Wang, X., & Ma, X. (2022). Design of a location-based opportunistic geographic routing protocol. Computer Communications, 181, 357–364. https://doi.org/10.1016/j.comcom.2021.10.030

    Article  Google Scholar 

  7. Jing, Z., Binbin, S., Wei, F., & Chengmin, W. (2021, April). GPSR protocol perimeter forwarding optimization algorithm based on game model in UAV network, In 2021 International Conference on Computer Technology and Media Convergence Design (CTMCD), pp. 148–153, IEEE

  8. Liu, C., Fang, D., Liu, X., Dan, X., Chen, X., Liang, C.-J.M., Liu, B., & Tang, Z. (2019). Low-cost and robust geographic opportunistic routing in a strip topology wireless network. ACM Transactions on Sensor Networks, 15(2), 1–27. https://doi.org/10.1145/3309701

    Article  Google Scholar 

  9. Al-Sulaifanie, A. I., Al-Sulaifanie, B. K., & Biswas, S. (2022). Recent trends in clustering algorithms for wireless sensor networks: A comprehensive review. Computer Communications, 191, 395–424. https://doi.org/10.1016/j.comcom.2022.05.006

    Article  Google Scholar 

  10. Zeng, Y., Yan, J., Huang, G., Liu, X., Zhou, H., & Liu, A. (2021). Traffic transfer assisted by super nodes for strip-shaped wireless sensor networks. IEEE Internet of Things Journal, 9(10), 7120–7127. https://doi.org/10.1109/JIOT.2021.3068217

    Article  Google Scholar 

  11. Srikanth, N., Prasad, M. S. G., & Sharma, D. K. (2020). A compressive family based efficient trust routing protocol (C-FETRP) for maximizing the lifetime of WSN. Data Communication and Networks, 1049, 69–80. https://doi.org/10.1007/978-981-15-0132-6_6

    Article  Google Scholar 

  12. Dutta, A. K., Albagory, Y., Alsanea, M., Sait, A. R. W., & AlRawashdeh, H. S. (2023). Fuzzy with metaheuristics based routing for clustered wireless sensor networks. Intelligent Automation and Soft Computing, 35(1), 367–380.

    Article  Google Scholar 

  13. Kumar, M. S., & Kumar, G. A. (2023). Efficient hybrid energy optimization method in location aware unmanned WSN. Intelligent Automation and Soft Computing, 35(1), 705–725.

    Article  Google Scholar 

  14. Prakash, P. S., Kavitha, D., & Reddy, P. C. (2022). Safe and secured routing using multi‐objective fractional artificial lion algorithm in WSN. Concurrency and Computation: Practice and Experience. https://doi.org/10.1002/cpe.7098

    Article  Google Scholar 

  15. Bangotra, D. K., Singh, Y., Kumar, N., Kumar Singh, P., & Ojeniyi, A. (2022). Energy-efficient and secure opportunistic routing protocol for WSN: Performance analysis with nature-inspired algorithms and its application in biomedical applications. BioMed Research International, 2022, 1976694. https://doi.org/10.1155/2022/1976694

    Article  Google Scholar 

  16. Li, N., Yuan, X., Martinez-Ortega, J. F., & Diaz, V. H. (2021). The network-based candidate forwarding set optimization for opportunistic routing. IEEE Sensors Journal, 21(20), 23626–23644. https://doi.org/10.1109/JSEN.2021.3105535

    Article  Google Scholar 

  17. Patil, P. A., Deshpande, R. S., & Mane, P. B. (2020). Trust and opportunity based routing framework in wireless sensor network using hybrid optimization algorithm. Wireless Personal Communications, 115(1), 415–437. https://doi.org/10.1007/s11277-020-07579-6

    Article  Google Scholar 

  18. Ramasamy, K., Anisi, M. H., & Jindal, A. (2021). E2DA: Energy efficient data aggregation and end-to-end security in 3D reconfigurable WSN. IEEE Transactions on Green Communications and Networking, 6(2), 787–798. https://doi.org/10.1109/TGCN.2021.3126786

    Article  Google Scholar 

  19. Liu, C., Fang, D., Chen, X., Hu, Y., Cui, W., Xu, G., & Chen, H. (2015). LSVS: Bringing layer slicing and virtual sinks to geographic opportunistic routing in strip WSNs. In 2015 IEEE Fifth International Conference on Big Data and Cloud Computing, pp. 281–286

  20. Yue, W., Zhang, P., Shao, F., Yin, Z., Sheng, X., & Li, J. (2016). Analysis of network reliability and lifetime on strip area in wireless sensor networks. DEStech Transactions on Engineering and Technology Research. https://doi.org/10.12783/dtetr/iect2016/3819

    Article  Google Scholar 

  21. Xin, H., & Liu, X. (2017). Energy-balanced transmission with accurate distances for strip-based wireless sensor networks. IEEE Access, 5, 16193–16204. https://doi.org/10.1109/ACCESS.2017.2728367

    Article  Google Scholar 

  22. Zhang, J. H., Yi, Z. X., & Peng, C. Y. (2020). An energy-aware data transmission scheme under the guarantee of reliability for 3D WSNs. Journal of Sensors, 2020(2020), 8855073. https://doi.org/10.1155/2020/8855073

    Article  Google Scholar 

  23. Ren, J., Zhang, Y., Zhang, K., Liu, A., Chen, J., & Shen, X. S. (2016). Lifetime and energy hole evolution analysis in data-gathering wireless sensor networks. IEEE Transactions on Industrial Informatics, 12(2), 788–800. https://doi.org/10.1109/TII.2015.2411231

    Article  Google Scholar 

Download references

Funding

The Funding was provided by National Natural Science Foundation of China, (Grant No. 61902432), Jinhuan Zhang

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hao Zhang.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, J., Chen, X., Wang, J. et al. A geodesic distance-based routing scheme for sensor networks with irregular terrain structure. Wireless Netw 29, 3207–3221 (2023). https://doi.org/10.1007/s11276-023-03377-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-023-03377-7

Keywords

Navigation