IJBTT

AI-Powered Networked Management: The Future of MVNOs and MVNAs
	© 2024 by IJCTT Journal
	Volume-72 Issue-8
	Year of Publication : 2024
	Authors : Karthick Cherladine
	DOI :  10.14445/22312803/IJCTT-V72I8P126

How to Cite?

Karthick Cherladine, "AI-Powered Networked Management: The Future of MVNOs and MVNAs," International Journal of Computer Trends and Technology, vol. 72, no. 8, pp. 180-189, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I8P126

Abstract
The changes that networked management system with AI brings to Mobile Virtual Network Operators (MVNOs) and Mobile Virtual Network Aggregators (MVNAs) signify a leap in the telecommunications business. The major use of artificial intelligence within the MVNO and the MVNA environment is in the machine learning and deep learning models that can be used to design the subsequent network efficiency, customer experience, and operation efficiency. AI figures within traffic predictability assist such entities to anticipate the degree of network density and allocate relevant resources to ensure that users do not encounter hitches. Fault management receives significant enhancements through artificial intelligence, especially when it imparts predictions for preventing network problems and their ultimate impacts on service continuity with minimal disruptions. Thirdly, of the invasive services based on artificial intelligence algorithms, the improvement in such indexes as customer satisfaction is high due to distinguishing between preferences and application patterns. This paper focuses on critical outcomes as it reveals how AI is embedded into the structure of operations in MVNOs and MVNAs, which briefly enables data evaluation and decision-making. Thus, the interaction between AI and network management introduces new opportunities for differentiation and the development of telecommunications technologies.

Keywords
AI-powered network management, Mobile Virtual Network Operators (MVNOs), Mobile Virtual Network Aggregators (MVNAs), Machine learning, Deep learning, Network optimization.

Reference

[1] Leonardo Militano et al., “AI-Powered Infrastructures for Intelligence and Automation in Beyond-5G Systems,” 2021 IEEE Globecom Workshops (GC Wkshps), Madrid, Spain, pp. 1-6, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[2] AI’s Role in Network Management, Dlink.[Online]. Available: https://www.dlink.com/uk/en/resource-centre/blog/ai-s-role-innetwork-management#:~:text=As%20networks%20continue%20to%20grow,the%20operation%20of%20the%20network
[3] Anand S. Rao, and Michael P. George, “Intelligent Real-Time Network Management,” Proceedings of the Tenth International Conference on AI, Expert Systems and Natural Language, pp. 1-16, 1991.
[Google Scholar] [Publisher Link]
[4] Yang Zhao et al., “Artificial Intelligence-Based Fault Detection and Diagnosis Methods for Building Energy Systems: Advantages, Challenges and the Future,” Renewable and Sustainable Energy Reviews, vol. 109, pp. 85-101, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Wayne W. Eckerson, “Predictive Analytics, Extending the Value of Your Data Warehousing Investment,” TDWI Best Practices Report, pp. 1-36, 2007.
[Google Scholar]
[6] MVNO White Papers, Plintron. [Online]. Available: https://plintron.com/insights/mvno-white-papers/
[7] Stanislav Hristov Ivanov, “Automated Decision-Making,” Foresight, vol. 25, no. 1, pp. 4-19, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Enhanced Network Management: Unleashing the Power of AI, Wholesale Orange, 2023. [Online]. Available: https://wholesale.orange.com/international/en/knowledge-hub/insights/enhanced-network-management-the-power-of-ai.html
[9] AI in Network Management Poses Challenges for Network Pros. [Online]. Available: https://wholesale.orange.com/international/en/knowledge-hub/insights/enhanced-network-management-the-power-of-ai.html
[10] Jianping Pan et al., “Network for AI and AI for Network: Challenges and Opportunities for Learning-Oriented Networks,” IEEE Network, vol. 35, no. 6, pp. 270-277, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[11] What is Artificial Intelligence in Networking?, Cisco. [Online]. Available: https://www.cisco.com/c/en/us/solutions/artificial-intelligence/artificial-intelligence-machine-learning-in-networking.html
[12] Traffic Prediction: How Machine Learning Helps Forecast Congestions and Plan Optimal Routes, AltexSoft, 2022. [Online]. Available: https://www.altexsoft.com/blog/traffic-prediction/
[13] What’s the Difference between MNO, MVNO & MVNA? Hologram. [Online]. Available: https://www.hologram.io/blog/mobile-network-operator/
[14] Challenges of Data Scalability, Medium. [Online]. Available: https://medium.com/@HirenDhaduk1/5-challenges-of-data-scalability-be23b74f90d1
[15] Top 11 New Technologies in AI: Exploring the Latest Trends. [Online]. Available: https://devabit.com/blog/top-11-new-technologies-in-ai-exploring-the-latest-trends/
[16] Mohammad Riyaz Belgaum et al., “Impact of Artificial Intelligence-Enabled Software-Defined Networks in Infrastructure and Operations: Trends and Challenges,” International Journal of Advanced Computer Science and Applications, vol. 12, no. 1, pp. 66- 73, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Adekunle Oyeyemi Adeniyi et al., “Ethical Considerations in Healthcare IT: A Review of Data Privacy and Patient Consent Issues,” World Journal of Advanced Research and Reviews, vol. 21, no. 2, pp. 1660-1668, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Navdeep Singh, and Daisy Adhikari, “Challenges and Solutions in Integrating AI with Legacy Inventory Systems,” International Journal for Research in Applied Science and Engineering Technology, vol. 11, no. 12, pp. 609-613, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Where Does TaaS Fit in With MNOs, MVNOs and MVNA/Es?, OXIO, 2024. [Online]. Available: https://oxio.com/blog/where-does-taas-fit-in-with-mnos-mvnos-mvnas/
[20] Future Trends of AI-driven Network Optimization, Spiceworks, 2024. [Online]. Available: https://www.spiceworks.com/tech/artificial-intelligence/guest-article/ai-driven-network-optimization/