International Journal of Computer Networks and Applications (IJCNA)

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ISSN : 2395-0455

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International Journal of Computer Networks and Applications (IJCNA)

International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

Performance Enhancement of Mobility-Enabled Wireless Sensor Network Using Sophisticated Eagle Search Optimization-Based Gaussian Ad Hoc On-Demand Distance Vector (SESO-GAODV) Routing Protocol

Author NameAuthor Details

V. Veerakumaran, Aruchamy Rajini

V. Veerakumaran[1]

Aruchamy Rajini[2]

[1]Department of Computer Science, Nallamuthu Gounder Mahalingam College, Pollachi, Tamil Nadu, India

[2]Department of Computer Science, Nallamuthu Gounder Mahalingam College, Pollachi, Tamil Nadu, India

Cite this Article

DOI: 10.22247/ijcna/2023/223428

Pages : 816-833

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Abstract

The research focuses on enhancing the performance of Mobility Enabled Wireless Sensor Networks (ME-WSNs) through the introduction of a novel routing protocol named Sophisticated Eagle Search Optimization-Based Gaussian Ad Hoc On-demand Distance Vector (SESO-GAODV). ME-WSNs pose unique challenges due to their dynamic and rapidly changing network topologies. To address these challenges, SESO-GAODV leverages the intelligent optimization techniques of Sophisticated Eagle Search Optimization and the dynamic route discovery capabilities of Gaussian Ad Hoc On-demand Distance Vector (GAODV). The proposed protocol undergoes extensive evaluations and comparisons with other existing routing protocols. Through comprehensive performance analysis, SESO-GAODV demonstrates superior results, including reduced delay, increased throughput, minimized packet loss, and lower energy consumption. The protocol's adaptability to changing network conditions and efficient handling of node mobility contribute to its energy-efficient nature, making it a promising solution for enhancing data transmission efficiency and reliability in ME-WSNs. SESO-GAODV's ability to optimize energy consumption ensures a prolonged network lifetime, facilitating seamless communication and optimized network performance in dynamic and challenging environments.

Index Terms

AODV

Eagle Search Optimization

Gaussian

ME-WSNs

Routing

Sensor Network

Reference

  1. 1.
    A. Islam, K. Akter, N. J. Nipu, A. Das, M. Mahbubur Rahman, and M. Rahman, “IoT Based Power Efficient Agro Field Monitoring and Irrigation Control System?: An Empirical Implementation in Precision Agriculture,” in 2018 International Conference on Innovations in Science, Engineering and Technology, ICISET 2018, 2018, pp. 372–377. doi: 10.1109/ICISET.2018.8745605.
  2. 2.
    N. Gharaei, Y. D. Al-Otaibi, S. A. Butt, S. J. Malebary, S. Rahim, and G. Sahar, “Energy-Efficient Tour Optimization of Wireless Mobile Chargers for Rechargeable Sensor Networks,” IEEE Syst. J., vol. 15, no. 1, pp. 27–36, 2021, doi: 10.1109/JSYST.2020.2968968.
  3. 3.
    J. Martin Sahayaraj and J. M. Ganaseakar, “Relay node selection with energy efficient routing using hidden Markov model in wireless sensor networks,” Int. J. Netw. Virtual Organ., vol. 19, no. 2–4, pp. 176–186, 2018, doi: 10.1504/IJNVO.2018.095420.
  4. 4.
    L. Rajaoarisoa, N. K. M’Sirdi, M. Sayed-Mouchaweh, and L. Clavier, “Decentralized fault-tolerant controller based on cooperative smart-wireless sensors in large-scale buildings,” J. Netw. Comput. Appl., vol. 214, p. 103605, 2023, doi: 10.1016/j.jnca.2023.103605.
  5. 5.
    F. Niaz, M. Khalid, Z. Ullah, N. Aslam, M. Raza, and M. K. Priyan, “A bonded channel in cognitive wireless body area network based on IEEE 802.15.6 and internet of things,” Comput. Commun., vol. 150, pp. 131–143, Jan. 2020, doi: 10.1016/j.comcom.2019.11.016.
  6. 6.
    T. Waheed, Aqeel-ur-Rehman, F. Karim, and S. Ghani, “QoS Enhancement of AODV Routing for MBANs,” Wirel. Pers. Commun., vol. 116, no. 2, pp. 1379–1406, Jan. 2021, doi: 10.1007/s11277-020-07558-x.
  7. 7.
    Y. Han, H. Hu, and M. Yao, “Trust-Aware Secure Routing Protocol for Wireless Sensor Networks,” Jisuanji Gongcheng/Computer Eng., vol. 47, no. 9, pp. 145–152, 2021, doi: 10.19678/j.issn.1000-3428.0058217.
  8. 8.
    G. Valecce, S. Strazzella, A. Radesca, and L. A. Grieco, “Solarfertigation: Internet of things architecture for smart agriculture,” in 2019 IEEE International Conference on Communications Workshops, ICC Workshops 2019 - Proceedings, 2019. doi: 10.1109/ICCW.2019.8756735.
  9. 9.
    L. Guezouli, K. Barka, S. Bouam, and A. Zidani, “A variant of random way point mobility model to improve routing in wireless sensor networks,” Int. J. Inf. Commun. Technol., vol. 13, no. 4, pp. 407–423, 2018, doi: 10.1504/IJICT.2018.095031.
  10. 10.
    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.
  11. 11.
    D. Jayaraj, J. Ramkumar, M. Lingaraj, and B. Sureshkumar, “AFSORP: Adaptive Fish Swarm Optimization-Based Routing Protocol for Mobility Enabled Wireless Sensor Network,” Int. J. Comput. Networks Appl., vol. 10, no. 1, pp. 119–129, Jan. 2023, doi: 10.22247/ijcna/2023/218516.
  12. 12.
    J. Ramkumar and R. Vadivel, “Multi-Adaptive Routing Protocol for Internet of Things based Ad Hoc Networks,” Wirel. Pers. Commun., vol. 120, no. 2, pp. 887–909, Apr. 2021, doi: 10.1007/s11277-021-08495-z.
  13. 13.
    B. Kang, C. Park, and H. Choo, “A Location Aware Fast PMIPv6 for Low Latency Wireless Sensor Networks,” IEEE Sens. J., vol. 19, no. 20, pp. 9456–9467, 2019, doi: 10.1109/JSEN.2019.2925637.
  14. 14.
    M. A. Uddin, A. Mansour, D. Le Jeune, and E. H. M. Aggoune, “Agriculture internet of things: AG-IoT,” in 2017 27th International Telecommunication Networks and Applications Conference, ITNAC 2017, 2017, vol. 2017-Janua, pp. 1–6. doi: 10.1109/ATNAC.2017.8215399.
  15. 15.
    P. K. Dalela et al., “Constraint-Driven IoT-Based Smart Agriculture for Better e-Governance,” Advances in Intelligent Systems and Computing, vol. 1077. pp. 177–186, 2020. doi: 10.1007/978-981-15-0936-0_18.
  16. 16.
    X. Liu, J. Yu, W. Zhang, and H. Tian, “Low-energy dynamic clustering scheme for multi-layer wireless sensor networks,” Comput. Electr. Eng., vol. 91, p. 107093, 2021, doi: 10.1016/j.compeleceng.2021.107093.
  17. 17.
    M. Boushaba, A. Hafid, and M. Gendreau, “Node stability-based routing in Wireless Mesh Networks,” J. Netw. Comput. Appl., vol. 93, pp. 1–12, 2017, doi: 10.1016/j.jnca.2017.02.010.
  18. 18.
    A. Chowdhury and D. De, “MSLG-RGSO: Movement score based limited grid-mobility approach using reverse Glowworm Swarm Optimization algorithm for mobile wireless sensor networks,” Ad Hoc Networks, vol. 106, p. 102191, 2020, doi: 10.1016/j.adhoc.2020.102191.
  19. 19.
    P. Maheshwari, A. K. Sharma, and K. Verma, “Energy efficient cluster based routing protocol for WSN using butterfly optimization algorithm and ant colony optimization,” Ad Hoc Networks, vol. 110, p. 102317, 2021, doi: 10.1016/j.adhoc.2020.102317.
  20. 20.
    J. Aranda, D. Mendez, H. Carrillo, and M. Schölzel, “A framework for multimodal wireless sensor networks,” Ad Hoc Networks, vol. 106, p. 102201, 2020, doi: 10.1016/j.adhoc.2020.102201.
  21. 21.
    K. Patil, M. Jafri, D. Fiems, and A. Marin, “Stochastic modeling of depth based routing in underwater sensor networks,” Ad Hoc Networks, vol. 89, pp. 132–141, 2019, doi: 10.1016/j.adhoc.2019.03.009.
  22. 22.
    X. Hao, N. Yao, L. Wang, and J. Wang, “Joint resource allocation algorithm based on multi-objective optimization for wireless sensor networks,” Appl. Soft Comput. J., vol. 94, p. 106470, 2020, doi: 10.1016/j.asoc.2020.106470.
  23. 23.
    M. R. Rahman, M. M. Islam, A. I. Pritom, and Y. Alsaawy, “ASRPH: Application Specific Routing Protocol for Health care,” Comput. Networks, vol. 197, p. 108273, 2021, doi: 10.1016/j.comnet.2021.108273.
  24. 24.
    P. Ghosh, H. Ren, R. Banirazi, B. Krishnamachari, and E. Jonckheere, “Empirical evaluation of the heat-diffusion collection protocol for wireless sensor networks,” Comput. Networks, vol. 127, pp. 217–232, 2017, doi: 10.1016/j.comnet.2017.08.018.
  25. 25.
    H. Liu and K. Y. Ki, “Application of wireless sensor network based improved immune gene algorithm in airport floating personnel positioning,” Comput. Commun., vol. 160, pp. 494–501, 2020, doi: 10.1016/j.comcom.2020.04.036.
  26. 26.
    B. Chakraborty, S. Verma, and K. P. Singh, “Temporal Differential Privacy in Wireless Sensor Networks,” J. Netw. Comput. Appl., vol. 155, p. 102548, 2020, doi: 10.1016/j.jnca.2020.102548.
  27. 27.
    J. Lu, L. Feng, J. Yang, M. M. Hassan, A. Alelaiwi, and I. Humar, “Artificial agent: The fusion of artificial intelligence and a mobile agent for energy-efficient traffic control in wireless sensor networks,” Futur. Gener. Comput. Syst., vol. 95, pp. 45–51, Apr. 2019, doi: 10.1016/j.future.2018.12.024.
  28. 28.
    N. Khernane, J. F. Couchot, and A. Mostefaoui, “Maximum network lifetime with optimal power/rate and routing trade-off for Wireless Multimedia Sensor Networks,” Comput. Commun., vol. 124, pp. 1–16, 2018, doi: 10.1016/j.comcom.2018.04.012.
  29. 29.
    N. V. S. S. R. Lakshmi, S. Babu, and N. Bhalaji, “Analysis of clustered QoS routing protocol for distributed wireless sensor network,” Comput. Electr. Eng., vol. 64, pp. 173–181, Nov. 2017, doi: 10.1016/j.compeleceng.2016.11.019.
  30. 30.
    F. Ullah, M. Zahid Khan, M. Faisal, H. U. Rehman, S. Abbas, and F. S. Mubarek, “An Energy Efficient and Reliable Routing Scheme to enhance the stability period in Wireless Body Area Networks,” Comput. Commun., vol. 165, pp. 20–32, 2021, doi: 10.1016/j.comcom.2020.10.017.
  31. 31.
    S. Doostali and S. M. Babamir, “An energy efficient cluster head selection approach for performance improvement in network-coding-based wireless sensor networks with multiple sinks,” Comput. Commun., vol. 164, pp. 188–200, 2020, doi: 10.1016/j.comcom.2020.10.014.
  32. 32.
    D. Wang, J. Liu, and D. Yao, “An energy-efficient distributed adaptive cooperative routing based on reinforcement learning in wireless multimedia sensor networks,” Comput. Networks, vol. 178, p. 107313, 2020, doi: 10.1016/j.comnet.2020.107313.
  33. 33.
    A. Rajini, N. Nithya “Hybrid Intrusion Detection System in IOT Network Environments” Compliance Engineering Journal, vol.10, no.11, pp.541-548, 2019.
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