International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

MENU
International Journal of Computer Networks and Applications (IJCNA)

International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

Energizing Firefly Optimization-Inspired Routing Protocol (EFOIRP) for Performance Enhancement in IOT-Based Cloud Wireless Sensor Networks (IC-WSN)

Author NameAuthor Details

J. Jerlin Adaikala Sundari, G. Preethi

J. Jerlin Adaikala Sundari[1]

G. Preethi[2]

[1]Department of Computer Technology, PSG College of Arts and Science, Coimbatore, Tamil Nadu, India.

[2]Department of Computer Science, PRIST University, Thanjavur, Tamil Nadu, India.

Cite this Article

DOI: 10.22247/ijcna/2024/224441

Pages : 140-158

 Download PDF

947

Views

Abstract

Physical obstructions that disrupt signal propagation and routing paths hinder routing performance in IoT-based Cloud Wireless Sensor Networks (IC-WSN) for greenhouse farming. Existing routing algorithms fail to address the energy consumption challenge, resulting in suboptimal routing paths and potential data loss. This paper proposes an Energizing Firefly Optimization-Inspired Routing Protocol (EFOIRP) to enhance performance in IC-WSN. The protocol employs novel routing strategies to handle physical obstructions within greenhouses. It includes comprehensive site surveys to identify obstructions and their impact on signal propagation, enabling intelligent path selection that minimizes obstruction effects and ensures reliable data transmission. This research aims to achieve seamless data transmission and monitoring in greenhouse farming. EFOIRP minimizes signal interference by addressing physical obstructions, optimizing data transmission efficiency, and empowering farmers with reliable and accurate data for precise control over greenhouse conditions and resource management. The research objectives encompass characterizing obstructions, developing adaptive routing algorithms, evaluating performance through simulations or experiments, investigating scalability, and validating effectiveness in real-world greenhouse farming scenarios. The proposed EFOIRP aims to overcome the limitations of existing routing algorithms and improve the performance of IC-WSN in greenhouse farming environments.

Index Terms

Cloud

Greenhouse

Firefly Optimization

IoT

Routing Protocol

Wireless Sensor Networks

Reference

  1. 1.
    P. Handayani and N. Folz, “Adaptive Land Management for Climate-Smart Agriculture,” in InHeNce 2021 - 2021 IEEE International Conference on Health, Instrumentation and Measurement, and Natural Sciences, 2021. doi: 10.1109/InHeNce52833.2021.9537265.
  2. 2.
    D. C. Magnaye, “Climate Smart Agriculture Edu-tourism: A Strategy to Sustain Grassroots Pro-biodiversity Entrepreneurship in the Philippines,” Advances in Science, Technology and Innovation. pp. 203–218, 2019. doi: 10.1007/978-3-030-10804-5_20.
  3. 3.
    A. A. Abdalla et al., “Microstructure, chemical compositions, and soft computing models to evaluate the influence of silicon dioxide and calcium oxide on the compressive strength of cement mortar modified with cement kiln dust,” Constr. Build. Mater., vol. 341, p. 127668, 2022, doi: 10.1016/j.conbuildmat.2022.127668.
  4. 4.
    C. Morales-Morales, P. R. Najera-Medina, M. Castro-Bello, J. Morales-Morales, and J. Hernandez-Romano, “Wireless Real-Time Monitoring System Applied in a Tomato Greenhouse,” in 2020 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2020, 2020, pp. 1–6. doi: 10.1109/ROPEC50909.2020.9258762.
  5. 5.
    C. Guo, Y. Zi, and W. Ren, “A Blockchain Based Framework for Smart Greenhouse Data Management,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12817 LNAI. pp. 299–310, 2021. doi: 10.1007/978-3-030-82153-1_25.
  6. 6.
    P. S. Georgantopoulos, D. Papadimitriou, C. Constantinopoulos, T. Manios, I. N. Daliakopoulos, and D. Kosmopoulos, “A Multispectral Dataset for the Detection of Tuta Absoluta and Leveillula Taurica in Tomato Plants,” Smart Agric. Technol., vol. 4, p. 100146, 2023, doi: 10.1016/j.atech.2022.100146.
  7. 7.
    A. Banerjee and D. M. Akbar Hussain, “SD-EAR: Energy aware routing in software defined wireless sensor networks,” Appl. Sci., vol. 8, no. 7, 2018, doi: 10.3390/app8071013.
  8. 8.
    D. Ardiansyah, A. S. Miftahul Huda, Darusman, R. G. Pratama, and A. P. Putra, “Wireless Sensor Network Server for Smart Agriculture Optimatization,” in IOP Conference Series: Materials Science and Engineering, 2019. doi: 10.1088/1757-899X/621/1/012001.
  9. 9.
    S. Hemavathi and B. Latha, FRHO: Fuzzy rule-based hybrid optimization for optimal cluster head selection and enhancing quality of service in wireless sensor network, vol. 79, no. 11. Springer, 2023, pp. 12238–12265. doi: 10.1007/s11227-023-05106-5.
  10. 10.
    S. B. Viswanath, T. M. Nagendrappa, and K. R. Venkatesh, “Jsmcrp: Cross-layer architecture based joint-synchronous mac and routing protocol for wireless sensor network,” ECTI Trans. Electr. Eng. Electron. Commun., vol. 19, no. 1, pp. 94–113, 2021, doi: 10.37936/ECTI-EEC.2021191.240719.
  11. 11.
    K. Haseeb, I. Ud Din, A. Almogren, I. Ahmed, and M. Guizani, “Intelligent and secure edge-enabled computing model for sustainable cities using green internet of things,” Sustain. Cities Soc., vol. 68, p. 102779, 2021, doi: 10.1016/j.scs.2021.102779.
  12. 12.
    L. Hong-tan, K. Cui-hua, B. A. Muthu, and C. B. Sivaparthipan, “Big data and ambient intelligence in IoT-based wireless student health monitoring system,” Aggression and Violent Behavior. Elsevier Ltd, 2021. doi: 10.1016/j.avb.2021.101601.
  13. 13.
    K. Murali Krishna, Y. D. Borole, S. Rout, P. Negi, M. Deivakani, and R. Dilip, “Inclusion of Cloud, Blockchain and IoT Based Technologies in Agriculture Sector,” in 2021 9th International Conference on Cyber and IT Service Management, CITSM 2021, 2021. doi: 10.1109/CITSM52892.2021.9588894.
  14. 14.
    S. Namani and B. Gonen, “Smart agriculture based on IoT and cloud computing,” in Proceedings - 3rd International Conference on Information and Computer Technologies, ICICT 2020, IEEE, Mar. 2020, pp. 553–556. doi: 10.1109/ICICT50521.2020.00094.
  15. 15.
    L. L. Hung, F. Y. Leu, K. L. Tsai, and C. Y. Ko, “Energy-efficient cooperative routing scheme for heterogeneous wireless sensor networks,” IEEE Access, vol. 8, pp. 56321–56332, 2020, doi: 10.1109/ACCESS.2020.2980877.
  16. 16.
    X. Fu, Y. Yang, and O. Postolache, “Sustainable multipath routing protocol for multi-sink wireless sensor networks in harsh environments,” IEEE Trans. Sustain. Comput., vol. 6, no. 1, pp. 168–181, 2021, doi: 10.1109/TSUSC.2020.2976096.
  17. 17.
    I. A. A. E. M. And and S. M. Darwish, “Towards Designing a Trusted Routing Scheme in Wireless Sensor Networks: A New Deep Blockchain Approach,” IEEE Access, vol. 9, pp. 103822–103834, 2021, doi: 10.1109/ACCESS.2021.3098933.
  18. 18.
    O. R. Ahutu and H. El-Ocla, “Centralized Routing Protocol for Detecting Wormhole Attacks in Wireless Sensor Networks,” IEEE Access, vol. 8, pp. 63270–63282, 2020, doi: 10.1109/ACCESS.2020.2983438.
  19. 19.
    M. Alotaibi, “Improved Blowfish Algorithm-Based Secure Routing Technique in IoT-Based WSN,” IEEE Access, vol. 9, pp. 159187–159197, 2021, doi: 10.1109/ACCESS.2021.3130005.
  20. 20.
    T. Zhao, L. Wang, K.-W. Chin, and C. Yang, “Routing in Energy Harvesting Wireless Sensor Networks With Dual Alternative Batteries,” IEEE Syst. J., vol. 15, no. 3, pp. 3970–3979, 2020, doi: 10.1109/jsyst.2020.3007166.
  21. 21.
    K. Ramasamy, M. H. Anisi, and A. Jindal, “E2DA: Energy Efficient Data Aggregation and End-to-End Security in 3D Reconfigurable WSN,” IEEE Trans. Green Commun. Netw., vol. 6, no. 2, pp. 787–798, 2022, doi: 10.1109/TGCN.2021.3126786.
  22. 22.
    T. M. Behera, S. K. Mohapatra, U. C. Samal, M. S. Khan, M. Daneshmand, and A. H. Gandomi, “I-SEP: An Improved Routing Protocol for Heterogeneous WSN for IoT-Based Environmental Monitoring,” IEEE Internet Things J., vol. 7, no. 1, pp. 710–717, 2020, doi: 10.1109/JIOT.2019.2940988.
  23. 23.
    C. Chen, L. C. Wang, and C. M. Yu, “D2CRP: A Novel Distributed 2-Hop Cluster Routing Protocol for Wireless Sensor Networks,” IEEE Internet Things J., vol. 9, no. 20, pp. 19575–19588, 2022, doi: 10.1109/JIOT.2022.3148106.
  24. 24.
    F. H. El-Fouly, R. A. Ramadan, and R. A. Ramadan, “E3AF: Energy Efficient Environment-Aware Fusion Based Reliable Routing in Wireless Sensor Networks,” IEEE Access, vol. 8, pp. 112145–112159, 2020, doi: 10.1109/ACCESS.2020.3003155.
  25. 25.
    J. Ramkumar, A. Senthilkumar, M. Lingaraj, R. Karthikeyan, and L. Santhi, “Optimal Approach for Minimizing Delays in Iot-Based Quantum Wireless Sensor Networks Using Nm-Leach Routing Protocol,” J. Theor. Appl. Inf. Technol., vol. 102, no. 3, pp. 1099–1111, 2024.
  26. 26.
    R. Jaganathan, V. Ramasamy, L. Mani, and N. Balakrishnan, “Diligence Eagle Optimization Protocol for Secure Routing (DEOPSR) in Cloud-Based Wireless Sensor Network,” Res. Sq., 2022, doi: 10.21203/rs.3.rs-1759040/v1.
  27. 27.
    J. Ramkumar and R. Vadivel, “Improved frog leap inspired protocol (IFLIP) – for routing in cognitive radio ad hoc networks (CRAHN),” World J. Eng., vol. 15, no. 2, pp. 306–311, 2018, doi: 10.1108/WJE-08-2017-0260.
  28. 28.
    L. Mani, S. Arumugam, and R. Jaganathan, “Performance Enhancement of Wireless Sensor Network Using Feisty Particle Swarm Optimization Protocol,” ACM Int. Conf. Proceeding Ser., pp. 1–5, Dec. 2022, doi: 10.1145/3590837.3590907.
  29. 29.
    R. Jaganathan and R. Vadivel, “Intelligent Fish Swarm Inspired Protocol (IFSIP) for Dynamic Ideal Routing in Cognitive Radio Ad-Hoc Networks,” Int. J. Comput. Digit. Syst., vol. 10, no. 1, pp. 1063–1074, 2021, doi: 10.12785/ijcds/100196.
  30. 30.
    K. Wang, C. M. Yu, and L. C. Wang, “DORA: A Destination-Oriented Routing Algorithm for Energy-Balanced Wireless Sensor Networks,” IEEE Internet Things J., vol. 8, no. 3, pp. 2080–2081, 2021, doi: 10.1109/JIOT.2020.3025039.
  31. 31.
    G. Tong, S. Zhang, W. Wang, and G. Yang, “A particle swarm optimization routing scheme for wireless sensor networks,” CCF Trans. Pervasive Comput. Interact., vol. 5, no. 2, pp. 125–138, 2023, doi: 10.1007/s42486-022-00118-1.
SCOPUS
SCImago Journal & Country Rank

Announcements

Archives

Downloads

Contact Us

Dr.M. Milton Joe
EverScience Publications,
Nagercoil, Tamilnadu,India

Talk to Us

+91 9442777224

Email Us

editor@ijcna.org

info@ijcna.org

info@everscience.org

Quick Links

Follow Us

Copyright © 2023; EverScience Publications

Designed & Maintained By Shiro Software Solutions