Fiber Broadband for Big Data–Powered Secure SAP Cloud Architecture using Machine Learning in Healthcare
DOI:
https://doi.org/10.15680/IJCTECE.2025.0806019Keywords:
fiber broadband, 5G networks, cloud connectivity, network integration, edge computing, network slicing, security, SDN, NFVAbstract
The convergence of high-capacity fiber broadband with next-generation 5G wireless networks represents a pivotal architectural transformation for achieving intelligent, secure cloud connectivity. Fiber broadband delivers unparalleled bandwidth and reliability, while 5G provides low latency, high throughput, and ubiquitous wireless access. Integrating these technologies supports a range of emerging applications—such as edge computing, autonomous systems, Internet of Things (IoT), and mission-critical services—requiring seamless, high-performance links to cloud infrastructure. This research explores the technical, architectural, and security implications of integrating fiber broadband and 5G networks, focusing on cloud-centric connectivity solutions that enhance performance, scalability, and trustworthiness. The study synthesizes existing literature to highlight key integration models, evaluates performance and security challenges, and proposes a methodology for assessing the benefits of convergence. The findings demonstrate that integrated fiber–5G solutions significantly improve throughput, reliability, and service quality while enabling advanced features such as network slicing, edge orchestration, and secure multi-access strategies. However, challenges remain, including infrastructure costs, interoperability complexity, and end-to-end security coordination. The research concludes with recommendations for deployment best practices and future research directions to advance intelligent, secure cloud connectivity powered by fiber broadband and 5G convergence.References
1. Liu, F., et al. (2022). Performance evaluation of integrated fiber-wireless networks. IEEE Access, 10, 54–65.
2. Niu, Z., et al. (2019). 5G ultra-dense networks. IEEE Wireless Communications, 26(3), 10–17.
3. Rizzo, F., et al. (2021). Edge computing and 5G convergence: Architectures and challenges. Computer Networks, 195.
4. Roh, W., et al. (2014). Millimeter-wave beamforming for 5G wireless. IEEE Communications Magazine, 52(12), 106–113.
5. Khan, M. I. (2025). Big Data Driven Cyber Threat Intelligence Framework for US Critical Infrastructure Protection. Asian Journal of Research in Computer Science, 18(12), 42-54.
6. Pandey, A., Chauhan, A., & Gupta, A. (2023). Voice Based Sign Language Detection For Dumb People Communication Using Machine Learning. Journal of Pharmaceutical Negative Results, 14(2).
7. Udayakumar, S. Y. P. D. (2023). User Activity Analysis Via Network Traffic Using DNN and Optimized Federated Learning based Privacy Preserving Method in Mobile Wireless Networks.
8. Poornima, G., & Anand, L. (2024, May). Novel AI Multimodal Approach for Combating Against Pulmonary Carcinoma. In 2024 5th International Conference for Emerging Technology (INCET) (pp. 1-6). IEEE.
9. Shafi, M., et al. (2017). 5G: A tutorial overview of standards, trials, and research. IEEE Journal on Selected Areas in Communications, 35(6), 1201–1221.
10. Gopinathan, V. R. (2024). AI-Driven Customer Support Automation: A Hybrid Human–Machine Collaboration Model for Real-Time Service Delivery. International Journal of Technology, Management and Humanities, 10(01), 67-83.
11. Rahman, M. R., Rahman, M., Rasul, I., Arif, M. H., Alim, M. A., Hossen, M. S., & Bhuiyan, T. (2024). Lightweight Machine Learning Models for Real-Time Ransomware Detection on Resource-Constrained Devices. Journal of Information Communication Technologies and Robotic Applications, 15(1), 17-23.
12. N. Mahajan, "Strategic governance of digital tokenization for scalable B2B payment infrastructure," J. Inf. Syst. Eng. Manage., vol. 2024, no. 1, 2024.
13. Ramalingam, S., Mittal, S., Karunakaran, S., Shah, J., Priya, B., & Roy, A. (2025, May). Integrating Tableau for Dynamic Reporting in Large-Scale Data Warehousing. In 2025 International Conference on Networks and Cryptology (NETCRYPT) (pp. 664-669). IEEE.
14. Sundaresh, G., Ramesh, S., Malarvizhi, K., & Nagarajan, C. (2025, April). Artificial Intelligence Based Smart Water Quality Monitoring System with Electrocoagulation Technique. In 2025 3rd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA) (pp. 1-6). IEEE.
15. Sudhan, S. K. H. H., & Kumar, S. S. (2015). An innovative proposal for secure cloud authentication using encrypted biometric authentication scheme. Indian journal of science and technology, 8(35), 1-5.
16. Manda, P. (2024). Navigating the Oracle EBS 12.1. 3 to 12.2. 8 Upgrade: Key Strategies for a Smooth Transition. International Journal of Technology, Management and Humanities, 10(02), 21-26.
17. Pimpale, S. (2025). A Comprehensive Study on Cyber Attack Vectors in EV Traction Power Electronics. arXiv preprint arXiv:2511.16399.
18. Potdar, A., Gottipalli, D., Ashirova, A., Kodela, V., Donkina, S., & Begaliev, A. (2025, July). MFO-AIChain: An Intelligent Optimization and Blockchain-Backed Architecture for Resilient and Real-Time Healthcare IoT Communication. In 2025 International Conference on Innovations in Intelligent Systems: Advancements in Computing, Communication, and Cybersecurity (ISAC3) (pp. 1-6). IEEE.
19. Kumar, R., Panda, M. R., & Sardana, A. (2025). Reinforcement Learning for Autonomous Data Pipeline Optimization in Cloud-Native Architectures. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 4(3), 97-102.
20. Hu, C., Deng, Y., Min, G., Huang, P., & Qin, X. (2018). QoS promotion in energy-efficient datacenters through peak load scheduling. IEEE Transactions on Cloud Computing, 9(2), 777-792.
21. Kesavan, E. (2022). An empirical research in software testing in fuzzy TOPICS method. REST Journal on Data Analytics and Artificial Intelligence, 1(3), 51–56. https://doi.org/10.46632/jdaai/1/3/7
22. Kavuru, Lakshmi Triveni. (2023). Agile Management Outside Tech: Lessons from Non-IT Sectors. International Journal of Multidisciplinary Research in Science Engineering and Technology. 10.15680/IJMRSET.2023.0607052.
23. Genne, S. (2025). Micro Frontend Architecture: Engineering Modular Solutions for Enterprise Web Applications. Journal Of Engineering And Computer Sciences, 4(7), 754-760.
24. Kusumba, S. (2025). Driving US Enterprise Agility: Unifying Finance, HR, and CRM with an Integrated Analytics Data Warehouse. IPHO-Journal of Advance Research in Science And Engineering, 3(11), 56-63.
25. Singh, A. (2024). Enhancing Cybersecurity for Digital Twins: Challenges and Solutions. IJSAT-International Journal on Science and Technology, 15(4).
26. Chivukula, V. (2021). Impact of Bias in Incrementality Measurement Created on Account of Competing Ads in Auction Based Digital Ad Delivery Platforms. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 4(1), 4345–4350.
27. Karnam, A. (2024). Engineering Trust at Scale: How Proactive Governance and Operational Health Reviews Achieved Zero Service Credits for Mission-Critical SAP Customers. International Journal of Humanities and Information Technology, 6(4), 60–67. https://doi.org/10.21590/ijhit.06.04.11
28. Natta, P. K. (2024). Closed-loop AI frameworks for real-time decision intelligence in enterprise environments. International Journal of Humanities and Information Technology, 6(3). https://doi.org/10.21590/ijhit.06.03.05
29. Cherukuri, B. R. (2025). Enhanced trimodal emotion recognition using multibranch fusion attention with epistemic neural networks and Fire Hawk optimization. Journal of Machine and Computer, 58, Article 202505005. https://doi.org/10.53759/7669/jmc202505005
30. Kasireddy, J. R. (2023). Operationalizing lakehouse table formats: A comparative study of Iceberg, Delta, and Hudi workloads. International Journal of Research Publications in Engineering, Technology and Management, 6(2), 8371–8381. https://doi.org/10.15662/IJRPETM.2023.0602002
31. Madabathula, L. (2024). Reusable streaming pipeline frameworks for enterprise lakehouse analytics. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(4), 8444–8451. https://doi.org/10.15662/IJEETR.2024.0604007
32. Navandar, P. (2022). The Evolution from Physical Protection to Cyber Defense. International Journal of Computer Technology and Electronics Communication, 5(5), 5730-5752.
33. Vimal Raja, G. (2022). Leveraging Machine Learning for Real-Time Short-Term Snowfall Forecasting Using MultiSource Atmospheric and Terrain Data Integration. International Journal of Multidisciplinary Research in Science, Engineering and Technology, 5(8), 1336-1339.
34. Fazilath, M., & Umasankar, P. (2025, February). Comprehensive Analysis of Artificial Intelligence Applications for Early Detection of Ovarian Tumours: Current Trends and Future Directions. In 2025 3rd International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1-9). IEEE.
35. Poornima, G., & Anand, L. (2024, April). Effective Machine Learning Methods for the Detection of Pulmonary Carcinoma. In 2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM) (pp. 1-7). IEEE.
36. Sudhan, S. K. H. H., & Kumar, S. S. (2016). Gallant Use of Cloud by a Novel Framework of Encrypted Biometric Authentication and Multi Level Data Protection. Indian Journal of Science and Technology, 9, 44.
37. Poornachandar, T., Latha, A., Nisha, K., Revathi, K., & Sathishkumar, V. E. (2025, September). Cloud-Based Extreme Learning Machines for Mining Waste Detoxification Efficiency. In 2025 4th International Conference on Innovative Mechanisms for Industry Applications (ICIMIA) (pp. 1348-1353). IEEE.
38. Taleb, T., et al. (2017). On multi-access edge computing: A survey of the emerging 5G network edge. IEEE Communications Surveys & Tutorials, 19(3), 1657–1681.
39. Vittal, H., et al. (2016). Optical transport networks: Trends and challenges. IEEE Communications Magazine, 54(2), 26–34.
40. Zhang, H., et al. (2020). Security frameworks for integrated 5G and cloud infrastructures. IEEE Transactions on Network and Service Management, 17(4), 2157–2170.
