A hybrid ANFIS reptile optimization algorithm for energy-efficient inter-cluster routing in internet of things-enabled wireless sensor networks (original) (raw)

Abstract

In recent decades, the Internet of Things-enabled Wireless Sensor Networks (IWSN) plays a dominant role in the evolution of industry 4.0 by developing numerous WSN-assisted IoT applications. The energy efficiency of the deployed nodes will be the major concern for IWSN owing to the restricted battery resources. The clustering is widely utilized as an adequate approach for designing energy-efficient IWSN. Nonetheless, anonymous actions like a frequent change of inter-cluster routing, path identification, and occurrence of the faulty node have a direct influence on the energy consumption and network stability of IWSN. In this paper, a novel energy-efficient inter-cluster routing and fault management has been proposed to prolong the Quality of Services of IWSN. Primarily, the proposed system implements the Hybrid ANFIS Reptile Optimization Algorithm for identifying the optimal route from cluster to sink. Afterward, the Tuned supervision-based fault diagnosis strategy can be carried out to diagnose the different faults like sensing fault, residual energy fault, and communication fault in IWSN. The evaluation of the proposed system is computed using 1000 nodes with two distinct sink positions. Finally, the performance results validate that the proposed model achieves a lesser energy consumption of 0.01 J than the existing inter-cluster routing algorithms.

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References

  1. Olivo B, Pan A (2022) Internet of Things: State-of-the-art, Computing Paradigms and Reference Architectures. IEEE Lat Am Trans 20:49–63
    Article Google Scholar
  2. Kranthi S, Kanchana M, Suneetha M (2022) An intelligent intrusion prediction and prevention system for software defined internet of things cloud networks. Peer-to-Peer Netw Appl 1–16. https://doi.org/10.1007/s12083-022-01374-9
  3. Bhaskar KB, Prasanth A, Saranya P (2022) An energy-efficient blockchain approach for secure communication in IoT-enabled electric vehicles. Int J Commun Syst 35(e5189):1–27
    Google Scholar
  4. Tiwari P, Kumar Gupta S, Pathak A (2022) Field-clustering with sleep awake mechanism with fuzzy in wireless sensor network. Peer-to-Peer Netw Appl 1–13. https://doi.org/10.1007/s12083-022-01384-7
  5. Sekar J, Aruchamy P (2022) An efficient clinical support system for heart disease prediction using TANFIS classifier. Comput Intell 38:610–640
    Article Google Scholar
  6. Shantha R, Mahender K, Jenifer A (2022) Security analysis of hybrid one time password generation algorithm for IoT data. AIP Conf Proc 2418(030021):1–10
    Google Scholar
  7. Gong Y, Lai G (2022) Low-energy clustering protocol for query-based wireless sensor networks. IEEE Sens J 22:9135–9145
    Article Google Scholar
  8. Singh J, Yadav S, Kanungo V (2021) A node overhaul scheme for energy efficient clustering in wireless sensor networks. IEEE Sensors Letters 5:1–6
    Article Google Scholar
  9. Hou J, Qiao J, Han X (2022) Energy-saving clustering routing protocol for wireless sensor networks using fuzzy inference. IEEE Sens J 22:2845–2857
    Article Google Scholar
  10. Prasanth A, Pavalarajan S (2019) Zone-based sink mobility in wireless sensor networks. Sens Rev 39:874–880
    Article Google Scholar
  11. Hriez S, Almajali S, Elgala H (2022) A novel trust-aware and energy-aware clustering method that uses stochastic fractal search in IoT-enabled wireless sensor networks. IEEE Syst J 16:2693–2704
    Article Google Scholar
  12. Zhu B, Bedeer E, Nguyen HH (2021) Improved soft-k-means clustering algorithm for balancing energy consumption in wireless sensor networks. IEEE Internet Things J 8:4868–4881
    Article Google Scholar
  13. Shah I, Maity T, Dohare Y (2022) ICIC: A dual mode intra-cluster and inter-cluster energy minimization approach for multihop WSN. IEEE Access 10:70581–70594
    Article Google Scholar
  14. Al-Zubi R, Kreishan A, Alawad MQ, Darabkh KA (2021) On the event reporting of intra/inter-cluster sensor networks. Proc IEEE Int IOT, Electron MechatronConf 1–6
  15. Paranjape S, Barani S, Sutaone M, Mukherji P (2016) Intra and inter cluster congestion control technique for mobile wireless sensor networks. Proc Conf Adv Sign Process 1–6
  16. Prasanth A, Jayachitra S (2020) A novel multi-objective optimization strategy for enhancing quality of service in IoT enabled WSN applications. Peer-to-Peer Network Appl 13:1905–1920
    Article Google Scholar
  17. Mukherjee P, Samant T, Swain T, Datta A (2017) SEP-V: A solution to energy efficient technique in intra-cluster cooperative communication for wireless sensor network. Proc IEEE IntConf IoT Soc Mob Anal Cloud 1–6
  18. Lavanya S, Prasanth A, Jayachitra S (2021) A Tuned classification approach for efficient heterogeneous fault diagnosis in IoT-enabled WSN applications. Measurement 183(109771):1–16
    Google Scholar
  19. Quoc D, Liu N, Guo D (2022) A hybrid fault-tolerant routing based on Gaussian network for wireless sensor network. J Commun Netw 24:37–46
    Article Google Scholar
  20. Abas𝚤kele s-Turgut I, Altan G (2021) A fully distributed energy-aware multi-level clustering and routing for WSN-based IoT. Trans Emerg Tel Tech 32:e4355:1–16
  21. Ta Bao T, Nguyen Binh L, Ngo Viet H (2021) Adaptive knowledge transfer in multifactorial evolutionary algorithm for the clustered minimum routing cost problem. Appl Soft Comput 105:e107253:1–19
  22. Loganathan S, Arumugam J, Chinnababu V (2021) An energy-efficient clustering algorithm with self-diagnosis data fault detection and prediction for wireless sensor networks. Concurrency and Computation: Practice and Experience 33(e6288):1–27
    Google Scholar
  23. Moussa N, El Alaoui EB (2021) A. DACOR: A distributed ACO-based routing protocol for mitigating the hot spot problem in fog-enabled WSN architecture, International Journal of Communication systems, 35:e5008: 1–29
  24. Naseem M, Ahamad G, Sharma S, Abbasi E (2021) EE-LB-AOMDV: An efficient energy constraints-based load-balanced multipath routing protocol for MANETs. Int J Commun Syst 34(e4946):1–13
    Google Scholar
  25. Dwivedi AK, Mehra PS, Pal O, Doja MN, Alam B (2021) EETSP: Energy-efficient two-stage routing protocol for wireless sensor network-assisted Internet of Things. Int J Commun Syst 34(e4965):1–15
    Google Scholar
  26. Thangaramya K, Kulothungan K, Logambigai R, Selvi M, Ganapathy S, Kannan A (2019) Energy aware cluster and neuro-fuzzy based routing algorithm for wireless sensor networks in IoT. Comput Netw 151:211–223
    Article Google Scholar
  27. Prasanth A, Pavalarajan S (2020) Implementation of efficient intra and inter-zone routing for extending network consistency in wireless sensor networks. J Circ Syst Comput 29(e2050129):1–19
    Google Scholar
  28. Ramin Y, Masoud S (2021) An optimal cluster-based routing algorithm for lifetime maximization of Internet of Things. J Parallel Distrib Comput 156:7–24
    Article Google Scholar
  29. Fang W, Zhang W, Yang W, Li Z, Gao W, Yang Y (2021) Trust management based and energy efficient hierarchical routing protocol in wireless sensor networks. Digit Commun Netw 7:470–478
    Article Google Scholar
  30. Pattnaik S, Sahu PK (2021) Adaptive Neuro-Fuzzy Inference System-Particle swarm optimization-based clustering approach and hybrid Moth-flame cuttlefish optimization algorithm for efficient routing in wireless sensor network. Int J Commun Syst 34(e4783):1–18
    Google Scholar
  31. Vazhuthi P, Manikandan SP (2022) An energy-efficient auto clustering framework for enlarging quality of service in internet of things-enabled wireless sensor networks using fuzzy logic system. Concurr Comput: Pract Exp 1–28
  32. Prasanth A (2021) Certain Investigations on energy-efficient fault detection and recovery management in underwater wireless sensor networks. J Circ Syst Comput 30(2150137):1–20
    Google Scholar

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The authors did not receive support from any organization for the submitted work.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, V.R.S. College of Engineering and Technology, Arasur, Tamil Nadu, India
    P. Paruthi Ilam Vazhuthi
  2. Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Sriperumbudur, Tamil Nadu, India
    A. Prasanth
  3. Department of Computer Engineering, New Horizon College of Engineering, Bengaluru, India
    S. P. Manikandan
  4. Department of Electronics and Communication Engineering, DMI College of Engineering, Chennai, Tamil Nadu, India
    K. K. Devi Sowndarya

Authors

  1. P. Paruthi Ilam Vazhuthi
  2. A. Prasanth
  3. S. P. Manikandan
  4. K. K. Devi Sowndarya

Contributions

P.Paruthi Ilam Vazhuthi: Conceptualization, Visualization, Methodology.

A.Prasanth: Software, Data Curation, Writing- Original draft preparation.

S.P.Manikandan: Investigation, Software, Validation.

K.K.Devi Sowndarya: Writing—Review & Editing.

Corresponding author

Correspondence toP. Paruthi Ilam Vazhuthi.

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Vazhuthi, P.P.I., Prasanth, A., Manikandan, S.P. et al. A hybrid ANFIS reptile optimization algorithm for energy-efficient inter-cluster routing in internet of things-enabled wireless sensor networks.Peer-to-Peer Netw. Appl. 16, 1049–1068 (2023). https://doi.org/10.1007/s12083-023-01458-0

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