International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

International Journal of Computer Networks and Applications (IJCNA)

International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

Enhanced Intelligent Water Drop Algorithm Optimized Routing (EIWDR) for Quality of Service Enhancement in Internet of Things-Based Wireless Sensor Networks (IWSN)

Author NameAuthor Details

D. Deepalakshmi, B. Pushpa

D. Deepalakshmi[1]

B. Pushpa[2]

[1]Department of Computer Science and Information Science, Annamalai University, Tamil Nadu, India

[2]Department of Computer Science and Information Science, Annamalai University, Tamil Nadu, India

Abstract

The Internet of Things (IoT) has transformed how humans engage with technology, allowing pervasive connection and data sharing. In the Wireless Sensor Networks (WSNs) framework, IoT-based applications have been created for several areas, including agriculture, where greenhouse automation has been deployed for enhanced agricultural yields. However, WSNs face significant challenges, such as limited resources, unpredictable communication, and energy consumption. These issues become more pronounced when applied to greenhouse agriculture due to interference, congestion, and quality of service (QoS) requirements. Therefore, efficient routing protocols are crucial to address these challenges. The proposed study addresses the routing issues in IoT-based WSNs (IWSN) for greenhouse agriculture. Specifically, the Enhanced Intelligent Water Drop Algorithm Optimized Routing (EIWDR) is proposed as a novel routing protocol to enhance the QoS in IoT-based WSNs. The EIWDR protocol utilizes the intelligent water drop algorithm to optimize the routing path selection. The algorithm prioritizes energy-efficient routing, selects the most reliable path with minimum delay and data loss, and balances network load to prevent congestion. The proposed protocol also uses a modified weight function to improve the routing performance when applied in IWSN. To test the efficacy of the EIWDR, simulation tests were conducted in the NS-3 simulator. The EIWDR protocol fares better regarding network lifetime, packet delivery ratio, energy consumption, and packet delay than other routing protocols. Improved greenhouse agricultural quality of service using IWSN is possible with the help of the proposed EIWDR protocol. With the help of intelligent routing algorithms, network resources are used effectively, data is sent reliably, and overall performance is enhanced.

Index Terms

IoT

WSN

Routing

Greenhouse

Agriculture

QoS

Reference

  1. 1.
    Inga, E., Inga, J., Ortega, A.: Novel approach sizing and routing of wireless sensor networks for applications in smart cities. Sensors. 21, (2021). https://doi.org/10.3390/s21144692.
  2. 2.
    Chen, C., Wang, L.C., Yu, C.M.: D2CRP: A Novel Distributed 2-Hop Cluster Routing Protocol for Wireless Sensor Networks. IEEE Internet Things J. 9, 19575–19588 (2022). https://doi.org/10.1109/JIOT.2022.3148106.
  3. 3.
    Amin, R., Pali, I., Sureshkumar, V.: Software-Defined Network enabled Vehicle to Vehicle secured data transmission protocol in VANETs. J. Inf. Secur. Appl. 58, 102729 (2021). https://doi.org/10.1016/j.jisa.2020.102729.
  4. 4.
    Namani, S., Gonen, B.: Smart Agriculture Based on IoT and Cloud Computing. In: 2020 3rd International Conference on Information and Computer Technologies (ICICT). pp. 553–556. IEEE (2020). https://doi.org/10.1109/ICICT50521.2020.00094.
  5. 5.
    Juan Núñez, V.M., Faruk Fonthal, R., Yasmín Quezada, L.M.: Design and Implementation of WSN and IoT for Precision Agriculture in Tomato Crops. In: 2018 IEEE ANDESCON, ANDESCON 2018 - Conference Proceedings (2018). https://doi.org/10.1109/ANDESCON.2018.8564674.
  6. 6.
    Patel, N.R., Kumar, S., Singh, S.K.: Energy and Collision Aware WSN Routing Protocol for Sustainable and Intelligent IoT Applications. IEEE Sens. J. 21, 25282–25292 (2021). https://doi.org/10.1109/JSEN.2021.3076192.
  7. 7.
    Ardiansyah, D., Miftahul Huda, A.S., Darusman, Pratama, R.G., Putra, A.P.: Wireless Sensor Network Server for Smart Agriculture Optimatization. In: IOP Conference Series: Materials Science and Engineering (2019). https://doi.org/10.1088/1757-899X/621/1/012001.
  8. 8.
    Ademaj, F., Rzymowski, M., Bernhard, H.P., Nyka, K., Kulas, L.: Relay-Aided Wireless Sensor Network Discovery Algorithm for Dense Industrial IoT Utilizing ESPAR Antennas. IEEE Internet Things J. 8, 16653–16665 (2021). https://doi.org/10.1109/JIOT.2021.3075346.
  9. 9.
    Singh, J.P., Gupta, A.K.: Energy Aware Cluster Head Selection and Multipath Routing Using Whale-based Tunicate Swarm Algorithm (WTSA) for Wireless Sensor Network. New Rev. Inf. Netw. 27, 1–29 (2022). https://doi.org/10.1080/13614576.2022.2039748.
  10. 10.
    Shirmohammadi, Z., Farmani, M., Mohseni, M., Rohbani, N.: A Cluster-Based Energy-Aware Routing Algorithm for Wireless Sensor Networks. Ad-Hoc Sens. Wirel. Networks. 53, 303–315 (2022). https://doi.org/10.32908/ahswn.v53.8249.
  11. 11.
    Osamy, W., Khedr, A.M.: FACS: Fairness aware clustering scheme for monitoring applications of internet of things based wireless sensor networks. J. King Saud Univ. - Comput. Inf. Sci. 34, 3615–3629 (2022). https://doi.org/10.1016/j.jksuci.2022.03.030.
  12. 12.
    Meenaakshi Sundhari, R.P., Jaikumar, K.: IoT assisted Hierarchical Computation Strategic Making (HCSM) and Dynamic Stochastic Optimization Technique (DSOT) for energy optimization in wireless sensor networks for smart city monitoring. Comput. Commun. 150, 226–234 (2020). https://doi.org/10.1016/j.comcom.2019.11.032.
  13. 13.
    Ghosh, N., Sett, R., Banerjee, I.: An efficient trajectory based routing scheme for delay-sensitive data in wireless sensor network. Comput. Electr. Eng. 64, 288–304 (2017). https://doi.org/10.1016/j.compeleceng.2017.06.003.
  14. 14.
    Qin, X., Huang, G., Zhang, B., Li, C.: Energy efficient data correlation aware opportunistic routing protocol for wireless sensor networks. Peer-to-Peer Netw. Appl. 14, 1963–1975 (2021). https://doi.org/10.1007/s12083-021-01124-3.
  15. 15.
    Ivanov, S., Balasubramaniam, S., Botvich, D., Akan, O.B.: Gravity gradient routing for information delivery in fog Wireless Sensor Networks. Ad Hoc Networks. 46, 61–74 (2016). https://doi.org/10.1016/j.adhoc.2016.03.011.
  16. 16.
    Singh, H., Singh, D.: Hierarchical clustering and routing protocol to ensure scalability and reliability in large-scale wireless sensor networks. J. Supercomput. 77, 10165–10183 (2021). https://doi.org/10.1007/s11227-021-03671-1.
  17. 17.
    Chanak, P., Banerjee, I., Bose, S.: An intelligent fault-tolerant routing scheme for Internet of Things-enabled wireless sensor networks. Int. J. Commun. Syst. 34, (2021). https://doi.org/10.1002/dac.4970.
  18. 18.
    Almuntasheri, S., Alenazi, M.J.F.: Software-Defined Network-Based Energy-Aware Routing Method for Wireless Sensor Networks in Industry 4.0. Appl. Sci. 12, (2022). https://doi.org/10.3390/app121910073.
  19. 19.
    Guo, Y., Hu, G., Shao, D.: Multi-Path Routing Algorithm for Wireless Sensor Network Based on Semi-Supervised Learning. Sensors. 22, (2022). https://doi.org/10.3390/s22197691.
  20. 20.
    Roberts, M.K., Ramasamy, P.: Optimized hybrid routing protocol for energy-aware cluster head selection in wireless sensor networks. Digit. Signal Process. A Rev. J. 130, (2022). https://doi.org/10.1016/j.dsp.2022.103737.
  21. 21.
    Thekiya, M.S., Nikose, M.D.: Energy efficient clustering routing protocol using novel admission allotment scheme (AAS) based intra-cluster communication for Wireless Sensor Network. Int. J. Inf. Technol. 14, 2815–2824 (2022). https://doi.org/10.1007/s41870-022-01086-6.
  22. 22.
    Sulaiman, Y.H., Rashid, S.A., Hamdi, M.M., Faiyadh, Z.O.A., Sadiq, A.S.J., Ahmed, A.J.: Hybrid security in AOMDV routing protocol with improved salp swarm algorithm in wireless sensor network. Bull. Electr. Eng. Informatics. 11, 2866–2875 (2022). https://doi.org/10.11591/eei.v11i5.3696.
  23. 23.
    Ramkumar, J., Vadivel, R.: Multi-Adaptive Routing Protocol for Internet of Things based Ad-hoc Networks. Wirel. Pers. Commun. 120, 887–909 (2021). https://doi.org/10.1007/s11277-021-08495-z.
  24. 24.
    Jaganathan, R., Vadivel, R.: Intelligent Fish Swarm Inspired Protocol (IFSIP) for Dynamic Ideal Routing in Cognitive Radio Ad-Hoc Networks. Int. J. Comput. Digit. Syst. 10, 1063–1074 (2021). https://doi.org/10.12785/ijcds/100196.
  25. 25.
    Ramkumar, J., Kumuthini, C., Narasimhan, B., Boopalan, S.: Energy Consumption Minimization in Cognitive Radio Mobile Ad-Hoc Networks using Enriched Ad-hoc On-demand Distance Vector Protocol. 2022 Int. Conf. Adv. Comput. Technol. Appl. ICACTA 2022. 1–6 (2022). https://doi.org/10.1109/ICACTA54488.2022.9752899.
  26. 26.
    Kaedi, M., Bohlooli, A., Pakrooh, R.: Simultaneous optimization of cluster head selection and inter-cluster routing in wireless sensor networks using a 2-level genetic algorithm. Appl. Soft Comput. 128, 109444 (2022). https://doi.org/10.1016/j.asoc.2022.109444.
  27. 27.
    Manoharan, G., Sumathi, A.: Efficient routing and performance amelioration using Hybrid Diffusion Clustering Scheme in heterogeneous wireless sensor network. Int. J. Commun. Syst. 35, (2022). https://doi.org/10.1002/dac.5281.
  28. 28.
    Meng, C.: A Novel Routing Algorithm with Bernoulli Sampling-based Link Quality Estimation in Wireless Sensor Networks. Wirel. Pers. Commun. 126, 2753–2779 (2022). https://doi.org/10.1007/s11277-022-09840-6.
  29. 29.
    Gulec, O.: Extending lifetime of Wireless Nano-Sensor Networks: An energy efficient distributed routing algorithm for Internet of Nano-Things. Futur. Gener. Comput. Syst. 135, 382–393 (2022). https://doi.org/10.1016/j.future.2022.05.009.
  30. 30.
    Yang, J.: An ellipse-guided routing algorithm in wireless sensor networks. Digit. Commun. Networks. 8, 770–777 (2022). https://doi.org/10.1016/j.dcan.2021.08.005.
  31. 31.
    Gupta, S.K., Kumar, S., Tyagi, S., Tanwar, S.: SSEER: Segmented sectors in energy efficient routing for wireless sensor network. Multimed. Tools Appl. 81, 34697–34715 (2022). https://doi.org/10.1007/s11042-021-11829-5.
  32. 32.
    Chen, W., Zhang, B., Yang, X., Fang, W., Zhang, W., Jiang, X.: C-EEUC: a Cluster Routing Protocol for Coal Mine Wireless Sensor Network Based on Fog Computing and 5G. Mob. Networks Appl. 27, 1853–1866 (2022). https://doi.org/10.1007/s11036-019-01401-9.
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