MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641073010 A) filed by Vels Institute Of Science Technology And Advanced Studies on June 12, 2026, for Cloud Failure Forecasting Evaluating Machine Learning Vs Deep Learning Approaches.
Inventors include Dr. R. Priya Anand; Dr H Jayamangala; Dr K. Nandhini; Dr. A. Poongodi; Dr. C. Meenakshi; Dr. V. Sumalatha; Dr. Lipsa Nayak; Dr. K. Kumutha; Susha K B; Siji Jose C; and Dr. Vediappan.
The application for the patent was published on June 26, 2026, under issue no. 26/2026.
Abstract: ABSTRACT Cloud computing has become the backbone of modem digital infrastructure, supporting critical applications, data storage, arid online services. However, cloud environments are susceptible to various failures, including hardware faults, software bugs, network disruptions, resource exhaustion, and service outages. These failures can lead to significant financial losses, degraded user experience, and violations of Service Leve~ Agreements (SLAs). Accurate prediction of cloud failures before they occur is therefore essential for ensuring reliability, availability, and efficient resource management. Recent advancements in Artificial Intelligence (AI) have enabled predictive maintenance and failure forecasting techniques that leverage historical system logs, performance metrics, and resource utilization data. Machine Learning (ML) and Deep Learning (DL) approaches have emerged as promising solutions for cloud failure prediction. This study evaluates and compares the effectiveness of traditional ML algorithms and advanced DL models in forecasting failures within cloud environments. The comparison is based on prediction accuracy, computational complexity, training requirements, scalability, and real-time deployment suitability. Keywords: Cloud Computing, Failure Prediction, Machine Learning, Deep Learning, Predictive Analytics, Resource Management, Artificial Intelligence
Disclaimer: Curated by HT Syndication.
