Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Cognitive Intelligent Decisions for Big Data and Cloud Computing in Industrial Applications using Trifold Algorithms

  • Correspondence
  • Published:
Cognitive Computation Aims and scope Submit manuscript

Abstract

In contemporary real-time applications, diminutive devices are increasingly employing a greater portion of the spectrum to transmit data despite the relatively small size of said data. The demand for big data in cloud storage networks is on the rise, as cognitive networks can enable intelligent decision-making with minimal spectrum utilization. The introduction of cognitive networks has facilitated the provision of a novel channel that enables the allocation of low power resources while minimizing path loss. The proposed method involves the integration of three algorithms to examine the process of big data. Whenever big data applications are examined then distance measurement, decisions mechanism and learning techniques from past data is much importance thus algorithms are chosen according to the requirements of big data and cloud storage networks. Further the effect of integration process is examined with three case studies that considers low resource, path loss and weight functions where optimized outcome is achieved in all defined case studies as compared to existing approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Algorithm 1
Fig. 3
Algorithm 2
Fig. 4
Algorithm 3
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Data Availability

Data will be made available based on request.

References

  1. Chaturvedi S, Tyagi S, Simmhan Y. Cost-effective sharing of streaming dataflows for iot applications. IEEE Trans Cloud Comput. 2021;9:1391–407. https://doi.org/10.1109/TCC.2019.2921371.

    Article  Google Scholar 

  2. Chen Y, Qiu Z. Cloud network and mathematical model calculation scheme for dynamic big data. IEEE Access. 2020;8:137322–9. https://doi.org/10.1109/ACCESS.2020.3009675.

    Article  Google Scholar 

  3. Josilo S, Dan G. Joint management of wireless and computing resources for computation offloading in mobile edge clouds. IEEE Trans Cloud Comput. 2021;9:1507–20. https://doi.org/10.1109/TCC.2019.2923768.

    Article  Google Scholar 

  4. Berisha B, Mëziu E, Shabani I. Big data analytics in Cloud computing: an overview. J Cloud Comput. 2022. https://doi.org/10.1186/s13677-022-00301-w.

    Article  Google Scholar 

  5. Kozić N, Blagojević V, Ivaniš P. Performance analysis of underlay cognitive radio system with self-sustainable relay and statistical csi. Sensors. 2021. https://doi.org/10.3390/s21113727.

    Article  Google Scholar 

  6. Takyi K, Bagga A. Real-time application clustering in wide area networks. Comput Electr Eng. 2020;85:1–15. https://doi.org/10.1016/j.compeleceng.2020.106691.

    Article  Google Scholar 

  7. Lemes AL, Guimarães DA, Masselli YMC. System-to-distribution parameter mapping for the Gini index detector test statistic via artificial neural networks. Comput Electr Eng. 2020;85: 106692. https://doi.org/10.1016/j.compeleceng.2020.106692.

    Article  Google Scholar 

  8. Gulzar W, Waqas A, Dilpazir H, Khan A, Alam A, Mahmood H. Power control for cognitive radio networks: a game theoretic approach. Wirel Pers Commun. 2022;123:745–59. https://doi.org/10.1007/s11277-021-09156-x.

    Article  Google Scholar 

  9. He J. Decision scheduling for cloud computing tasks relying on solving large linear systems of equations. Comput Intell Neurosci. 2022. https://doi.org/10.1155/2022/3411959.

    Article  Google Scholar 

  10. Chen X. Big Data integration method of mathematical modeling and manufacturing system based on fog calculation. Math Probl Eng. 2021. https://doi.org/10.1155/2021/9987714.

    Article  Google Scholar 

  11. Xu S, Guo C. Computation offloading in a cognitive vehicular networks with vehicular cloud computing and remote cloud computing. Sensors (Switzerland). 2020;20:1–28. https://doi.org/10.3390/s20236820.

    Article  Google Scholar 

  12. Altrad O, Muhaidat S. A new mathematical analysis of the probability of detection in cognitive radio over fading channels. Eurasip J Wirel Commun Netw. 2013;2013:1–11. https://doi.org/10.1186/1687-1499-2013-159.

    Article  Google Scholar 

  13. Yau KLA, Goh HG, Chieng D, Kwong KH. Application of reinforcement learning to wireless sensor networks: models and algorithms. Computing. 2015;97:1045–75. https://doi.org/10.1007/s00607-014-0438-1.

    Article  MathSciNet  Google Scholar 

  14. Lorincz J, Ramljak I, Begusic D. Algorithm for evaluating energy detection spectrum sensing performance of cognitive radio MIMO-OFDM systems. Sensors. 2021;21:1–22. https://doi.org/10.3390/s21206881.

    Article  Google Scholar 

  15. Hassija V, Chamola V, Mahapatra A, Singal A, Goel D, Huang K, et al. Interpreting black-box models: a review on explainable artificial intelligence. Cognit Comput [Internet]. 2024;16:45–74. https://doi.org/10.1007/s12559-023-10179-82.

    Article  Google Scholar 

  16. Foggia P, Greco A, Roberto A, Saggese A, Vento M. Identity, Gender, Age, and Emotion recognition from speaker voice with multi-task deep networks for cognitive robotics. Cognit Comput. 2024.

  17. La V, Vincenzo G, Marco M, Giancarlo P. An eXplainable artificial intelligence methodology on big data architecture. 2024.

  18. Chatterjee S, Roy A, Roy SK, Misra S, Bhogal MS, Daga R. Big-sensor-cloud infrastructure: a holistic prototype for provisioning sensors-as-a-service. IEEE Trans Cloud Comput. 2021;9:1323–34. https://doi.org/10.1109/TCC.2019.2908820.

    Article  Google Scholar 

  19. Almagrabi H, Alshareef AM, Manoharan H, Mujlid H, Yafoz A, Selvarajan S. Empirical compression features of mobile computing and data applications using deep neural networks 2022;2022.

  20. Hasanin T, Manoharan H, Alterazi HA, Srivastava G, Selvarajan S, Lin JCW. Mathematical approach of fiber optics for renewable energy sources using general adversarial networks. Front Ecol Evol. 2023. https://doi.org/10.3389/fevo.2023.1132678.

    Article  Google Scholar 

  21. Khalil U, Ahmad A, Abdel-Aty AH, Elhoseny M, El-Soud MWA, Zeshan F. Identification of trusted IoT devices for secure delegation. Comput Electr Eng. 2021. https://doi.org/10.1016/j.compeleceng.2021.106988.

    Article  Google Scholar 

Download references

Acknowledgements

The authors of this study extend their appreciation to the Researchers Supporting Project number RSPD2024R544, King Saud University, Riyadh, Saudi Arabia."

Funding

The research is funded by the Researchers Supporting Project number (RSPD2024R544), King Saud University, Riyadh, Saudi Arabia.

Author information

Authors and Affiliations

  1. School of Built Environment, Engineering and Computing, Leeds Beckett University, LS1 3HE, Leeds, UK

    Shitharth Selvarajan

  2. Department of Electronics and Communication Engineering, Panimalar Engineering College, Poonamallee-600123, Chennai, Tamil Nadu, India

    Hariprasath Manoharan

  3. Computer Skills, Self-Development Skills Department, Deanship of Common First Year, King Saud University, 11362, Riyadh, Saudi Arabia

    Rakan A. Alsowail & Saravanan Pandiaraj

  4. Department of CSE, University Centre for Research & Development, Chandigarh University, Mohali, Punjab, 140413, India

    Achyut Shankar

  5. School of Computer Science Engineering, Lovely Professional University, Punjab, Phagwara, 144411, India

    Achyut Shankar

  6. Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, 248002, India

    Achyut Shankar

  7. Secure Cyber Systems Research Group (SCSRG), WMG, University of Warwick, Coventry, UK

    Carsten Maple

  8. Chulalongkorn Business School, Faculty of Commerce and Accountancy, Chulalongkorn University, Bangkok, Thailand

    Wattana Viriyasitavat

Authors
  1. Shitharth Selvarajan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hariprasath Manoharan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rakan A. Alsowail
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Achyut Shankar
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Saravanan Pandiaraj
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Carsten Maple
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Wattana Viriyasitavat
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shitharth Selvarajan.

Ethics declarations

Competing Interests

We declare that the authors have no competing interests as defined by Springer, or other interests that might be perceived to influence the results and/or discussion reported in this paper.

Institutional Review Board Statement

 Not applicable.

Informed Consent Statement

Not applicable.

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

Selvarajan, S., Manoharan, H., Alsowail, R.A. et al. Cognitive Intelligent Decisions for Big Data and Cloud Computing in Industrial Applications using Trifold Algorithms. Cogn Comput 16, 2967–2981 (2024). https://doi.org/10.1007/s12559-024-10317-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12559-024-10317-w

Keywords

Search

Navigation