Skip to main content

Advertisement

SpringerLink
Log in

Node Layout Optimization Strategy Based on Aquaculture Water Quality Monitoring System

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Due to the complex environment in the field, the number of nodes and the energy consumption of nodes should be considered in the deployment of aquaculture water quality monitoring system. Therefore, according to the actual network framework of aquaculture water quality monitoring system, based on the energy balance mechanism of clustering routing protocol, clustering mode and path energy consumption model, a new node layout and energy consumption optimization strategy is proposed in this paper, by improving artificial bee colony algorithm and genetic algorithm, the number of relay nodes and energy consumption of network are reduced. Through simulation and comparison, it is verified that the network coverage can be increased by 36.92% when the proposed optimization strategy and PSO perform the node placement task in the same scenario. The improved artificial bee colony algorithm has a significant improvement in the network coverage of the monitored area with the same number of nodes. On the basis of this, the final node layout scheme obtained by GA extends the life cycle of the network to a certain extent, and proves the guidance and application value of the strategy in the process of system building.

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

Similar content being viewed by others

Data Availability

The data that support the findings of this study are available on request from the corresponding author, upon reasonable request.

Code Availability

Code is available on genuine request.

References

  1. Zhao, Z., Shi, D., Hui, G., et al. (2019). An energy-optimization clustering routing protocol based on dynamic hierarchical clustering in 3D WSNs. IEEE Access, 7, 80159–80173.

    Article  Google Scholar 

  2. Wu, D., Geng, S., Cai, X., et al. (2020). A many-objective optimization WSN energy balance model. KSII Transactions on Internet and Information Systems (TIIS), 14(2), 514–537.

    Google Scholar 

  3. Prajapati, A., Kumar, V., Rajpoot, P., et al. (2019). Multi-objective heterogeneous clustering approach for efficient-energy optimization in WSN. In 2019 9th International conference on cloud computing, data science and engineering (confluence). IEEE, pp. 85–91.

  4. Agbehadji, I. E., Millham, R. C., Fong, S. J., et al. (2019). Multi-stage clustering algorithm for energy optimization in wireless sensor networks. In International conference on soft computing in data science. Springer, Singapore, pp. 223–238.

  5. Sembroiz, D., Careglio, D., Ricciardi, S., et al. (2019). Planning and operational energy optimization solutions for smart buildings. Information Sciences, 476, 439–452.

    Article  Google Scholar 

  6. Yue, C., Haifeng, W., Jianxinj, J., Kai, K. (2020). A water quality monitoring IOT system based on massive heterogeneous sensors. Computer Applications and Software 37(05), 1–37.

  7. Wardhana, R. (2020). Pemodelan multi-layer multihop routing protocol Pada Jaringan wireless sensor network. Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer, 15(1), 59–65.

    Google Scholar 

  8. Sharma, D. K., Dhurandher, S. K., Agarwal, D., et al. (2019). kROp: k-Means clustering based routing protocol for opportunistic networks. Journal of Ambient Intelligence and Humanized Computing, 10(4), 1289–1306.

    Article  Google Scholar 

  9. Behera, T. M., Mohapatra, S. K., Samal, U. C., et al. (2019). I-SEP: An improved routing protocol for heterogeneous WSN for IoT-based environmental monitoring. IEEE Internet of Things Journal, 7(1), 710–717.

    Article  Google Scholar 

  10. Fu, X., Fortino, G., Pace, P., et al. (2020). Environment-fusion multipath routing protocol for wireless sensor networks. Information Fusion, 53, 4–19.

    Article  Google Scholar 

  11. Cai, X., Sun, Y., Cui, Z., et al. (2019). Optimal LEACH protocol with improved bat algorithm in wireless sensor networks. KSII Transactions on Internet and Information Systems (TIIS), 13(5), 2469–2490.

    Google Scholar 

  12. Saxena, M., Joshi, A., Dutta, S., et al. (2021). Comparison of different multi-hop algorithms to improve the efficiency of LEACH protocol. Wireless Personal Communications, pp. 1–14.

  13. Sharma, D., Tomar, G. S. (2020). Enhance PEGASIS algorithm for increasing the life time of wireless sensor network. Materials Today: Proceedings, 29, 372–380.

  14. Santana, C. J., Jr., Macedo, M., Siqueira, H., et al. (2019). A novel binary artificial bee colony algorithm. Future Generation Computer Systems, 98, 180–196.

    Article  Google Scholar 

  15. Wang, H., Wang, W., Xiao, S., et al. (2020). Improving artificial bee colony algorithm using a new neighborhood selection mechanism. Information Sciences, 527, 227–240.

    Article  MathSciNet  Google Scholar 

  16. Balaji, S., Julie, E. G., & Robinson, Y. H. (2019). Development of fuzzy based energy efficient cluster routing protocol to increase the lifetime of wireless sensor networks. Mobile Networks and Applications, 24(2), 394–406.

    Article  Google Scholar 

  17. Wang, Z., Zhang, M., Gao, X., et al. (2019). A clustering WSN routing protocol based on node energy and multipath. Cluster Computing, 22(3), 5811–5823.

    Article  Google Scholar 

  18. Wang, Q., Lin, D., Yang, P., et al. (2019). An energy-efficient compressive sensing-based clustering routing protocol for WSNs. IEEE Sensors Journal, 19(10), 3950–3960.

    Article  Google Scholar 

  19. Martinez, B., Adelantado, F., Bartoli, A., et al. (2019). Exploring the performance boundaries of NB-IoT. IEEE Internet of Things Journal, 6(3), 5702–5712.

    Article  Google Scholar 

  20. Zhan, Q. I., He, N., Chen, Z., et al. Research on ZigBee-based remote water temperature monitoring and control system. In 2021 IEEE 2nd international conference on big data, artificial intelligence and internet of things engineering (ICBAIE). IEEE, pp. 1074–1077.

  21. Sinha, R. S., Wei, Y., & Hwang, S. H. (2017). A survey on LPWA technology: LoRa and NB-IoT. Ict Express, 3(1), 14–21.

    Article  Google Scholar 

  22. Qin, Z. (2019). Design and implementation of low-power aquaculture water quality monitoring system based on LoRa. Shanghai Ocean University.

Download references

Funding

This work was supported by Hunan Province Natural Science Foundation (No. 2021JJ31142). This work was supported also by Scientific Research Project of Hunan Provincial Department of Education (No. 19C1904).

Author information

Authors and Affiliations

  1. School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha, China

    Feng Jiang, Kaiyue Sha, Cong Lin & Zhao Wu

Authors
  1. Feng Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kaiyue Sha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Cong Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhao Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Feng Jiang or Cong Lin.

Ethics declarations

Conflict of interest

The authors declare that they have no known competing financial interests or potential conflicts.

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

Jiang, F., Sha, K., Lin, C. et al. Node Layout Optimization Strategy Based on Aquaculture Water Quality Monitoring System. Wireless Pers Commun 132, 2839–2856 (2023). https://doi.org/10.1007/s11277-023-10745-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-023-10745-1

Keywords

Search

Navigation