Skip to main content
SpringerLink
Log in

Fuzzy logic hybridized artificial intelligence for computing and networking on internet of things platform

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

Abstract

Artificial intelligence Computerized modelling is the best solution to manage immense information and storage in the IoT Network. Furthermore, IoT these days becoming more increasingly well-known with the development of high speed web systems and many advanced sensors that can be coordinated into a microcontroller. The information flows in the virtual environment presently will have these sensors data and the client information that can be send and receive information from the workstations using the peer to peer networking and computing. With the increase in the quantity of workstation and an ever increasing number of sensors, a few information might confront issues on the storage, delay, area constraint and congestion in the systems. To keep away from these issues, numerous mathematical calculations have been proposed in the recent past which has not been developed an fruitful solution for this issues.. In this work, an advanced fuzzy hybridized Artificial Intelligence system has been proposed to management the request on IoT platform. The significance of request management and computing has been processed in this paper. The experiment results show prominent outcomes than traditional methods.

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
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Lee I (2019) The internet of things for enterprises: an ecosystem, architecture, and IoT service business model. Internet of Things 7:100078

    Article  Google Scholar 

  2. Kim H, Ahmad A, Hwang J, Baqa H, Gall FL, Ortega MAR, Song J (2018) IoT-TaaS: towards a prospective IoT testing framework. IEEE Access 6:15480–15493

    Article  Google Scholar 

  3. Incki K, Ari I (2018) A novel runtime verification solution for IoT systems. IEEE Access 6:13501–13512

    Article  Google Scholar 

  4. Li X, Lian Z, Qin X, Jie W (2018) Topology-aware resource allocation for IoT services in clouds. IEEE Access 6:77880–77889

    Article  Google Scholar 

  5. Truong H-L, Narendra NC, Lin K-J (2018) Notes on ensembles of IoT, network functions and clouds for service-oriented computing and applications. SOCA 12(1):1–10

    Article  Google Scholar 

  6. Baskar S, Periyanayagi S, Shakeel PM, Dhulipala VS (2019) An energy persistent range-dependent regulated transmission communication model for vehicular network applications. Comput Netw. https://doi.org/10.1016/j.comnet.2019.01.027

  7. Bello O, Zeadally S (2019) Toward efficient smartification of the Internet of Things (IoT) services. Futur Gener Comput Syst 92:663–673

    Article  Google Scholar 

  8. Preeth SKSL, Dhanalakshmi R, Kumar R, Shakeel PM An adaptive fuzzy rule based energy efficient clustering and immune-inspired routing protocol for WSN-assisted IoT system. J Ambient Intell Humaniz Comput 2018:1–13. https://doi.org/10.1007/s12652-018-1154-z

  9. Khansari ME, Sharifian S, Motamedi SA (2018) Virtual sensor as a service: a new multicriteria QoS-aware cloud service composition for IoT applications. J Supercomput 74(10):5485–5512

    Article  Google Scholar 

  10. Zhang D, Qiao Y, She L, Shen R, Ren J, Zhang Y (2019) Two time-scale resource management for Green Internet of Things Networks. IEEE Internet Things J 6(1):545–556

    Article  Google Scholar 

  11. Munoz R, Vilalta R, Yoshikane N, Casellas R, Martinez R, Tsuritani T, Morita I (2018) Integration of IoT, transport SDN, and edge/cloud computing for dynamic distribution of IoT analytics and efficient use of network resources. J Lightwave Technol 36(7):1420–1428

    Article  Google Scholar 

  12. Shah-Mansouri H, Wong VWS (2018) Hierarchical fog-cloud computing for IoT systems: a computation offloading game. IEEE Internet Things J 5(4):3246–3257

    Article  Google Scholar 

  13. Terroso-Saenz F, González-Vidal A, Ramallo-González AP, Skarmeta AF (2019) An open IoT platform for the management and analysis of energy data. Futur Gener Comput Syst 92:1066–1079

    Article  Google Scholar 

  14. Sodhro AH, Pirbhulal S, Luo Z, de Albuquerque VHC (2019) Towards an optimal resource management for IoT based green and sustainable smart cities. J Clean Prod 220:1167–1179

    Article  Google Scholar 

  15. Kim H-W, Park JH, Jeong Y-S (2019) Adaptive job allocation scheduler based on usage pattern for computing offloading of IoT. Futur Gener Comput Syst 98:18–24

    Article  Google Scholar 

  16. Lopez D, Gunasekaran M Assessment of vaccination strategies using fuzzy multi-criteria decision making. 5th international conference on fuzzy and neural computing, Institute for Development & Research in Banking Technolog, Hyderabad, India. Adv Intell Syst Comput 415:195–208

  17. Guo H, Ren J, Zhang D, Zhang Y, Hu J (2018) A scalable and manageable IoT architecture based on transparent computing. J Parallel Distrib Comput 118:5–13

    Article  Google Scholar 

  18. Al-Qerem A, Alauthman M, Almomani A, Gupta BB (2019) IoT transaction processing through cooperative concurrency control on fog–cloud computing environment. Soft Comput

  19. Baskar S, Dhulipala VS, Shakeel PM, Sridhar KP, Kumar R (2019) Hybrid fuzzy based spearman rank correlation for cranial nerve palsy detection in MIoT environment. Health Technol, 1–12

  20. Kim J, Jeon Y, Kim H (2016) The intelligent IoT common service platform architecture and service implementation. J Supercomput 74(9):4242–4260

    Article  Google Scholar 

  21. Casadei R, Fortino G, Pianini D, Russo W, Savaglio C, Viroli M (2019) Modelling and simulation of opportunistic IoT services with aggregate computing. Futur Gener Comput Syst 91:252–262

    Article  Google Scholar 

  22. Sosa-Reyna CM, Tello-Leal E, Lara-Alabazares D (2018) Methodology for the model-driven development of service oriented IoT applications. J Syst Archit 90:15–22

    Article  Google Scholar 

  23. Gunasekaran M, Varatharajan R, Priyan MK (2018) Hybrid recommendation system for heart disease diagnosis based on multiple kernel learning with adaptive neuro-fuzzy inference system. Multimed Tools Appl 77(4):4379–4399

    Article  Google Scholar 

  24. Mohamed Shakeel P, Baskar S, Selvakumar S. Wireless Pers Commun (2019) Retrieving multiple patient information by using the virtual MIMO and path Beacon in wireless body area network, pp 1–12. https://doi.org/10.1007/s11277-019-06525-5

  25. Guo H, Liu J, Zhang J, Sun W, Kato N (2018) Mobile-edge computation offloading for Ultradense IoT networks. IEEE Internet Things J 5(6):4977–4988

    Article  Google Scholar 

  26. Cheng B, Solmaz G, Cirillo F, Kovacs E, Terasawa K, Kitazawa A (2018) FogFlow: easy programming of IoT services over cloud and edges for smart cities. IEEE Internet Things J 5(2):696–707

    Article  Google Scholar 

  27. Ngan RT, Ali M, Fujita H, Giang NL, Manogaran G, Priyan MK (2019) A new representation of intuitionistic fuzzy systems and their applications in critical decision making. IEEE Intell Syst

  28. Abdel-Basset M, Manogaran G, Gamal A, Chang V (2019) A novel intelligent medical decision support model based on soft computing and IoT. IEEE Internet Things J

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, 150080, China

    Hongzhuo Qi

Authors
  1. Hongzhuo Qi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hongzhuo Qi.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qi, H. Fuzzy logic hybridized artificial intelligence for computing and networking on internet of things platform. Peer-to-Peer Netw. Appl. 13, 2078–2088 (2020). https://doi.org/10.1007/s12083-019-00827-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-019-00827-y

Keywords

Search

Navigation