Building Adaptive Networking Protocols with AI-Powered Anomaly Detection for Autonomous Infrastructure Management

Authors

  • Srinivas Kalyan Yellanki

Keywords:

Adaptive Networking,Anomaly Detection,Autonomous Infrastructure,Artificial Intelligence,Machine Learning,Self Healing Networks,Network Protocol Design,Infrastructure Management,Reinforcement Learning,Unsupervised Learning,Fault Tolerance,AI-Driven Optimization,Real-Time Monitoring,Cybersecurity,Intelligent Systems.

Abstract

The increasing complexity and scale of modern network infrastructures necessitate intelligent and adaptive systems capable of
self-management. This research presents a novel framework for developing adaptive networking protocols integrated with AI
powered anomaly detection to enhance the autonomy

References

Polineni, T. N. S., Ganti, V. K. A. T., Maguluri, K. K., & Rani, P. S. (2024). AI-Driven Analysis of Lifestyle Patterns for Early Detection of Metabolic Disorders. Journal of Computational Analysis and Applications, 33(8).

Sondinti, K., & Reddy, L. (2024). Financial Optimization in the Automotive Industry: Leveraging Cloud-Driven Big Data and AI for Cost Reduction and Revenue Growth. Financial Optimization in the Automotive Industry: Leveraging Cloud-Driven Big Data and AI for Cost Reduction and Revenue Growth (December 17, 2024)

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Published

2024-12-25

How to Cite

Srinivas Kalyan Yellanki. (2024). Building Adaptive Networking Protocols with AI-Powered Anomaly Detection for Autonomous Infrastructure Management . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 3116–3130. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2423

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Section

Articles