MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641078252 A) filed by Vardhaman College Of Engineering on June 25, 2026, for A System And Method For Intelligent Cloud Resource Allocation And Energy-Efficient Workload Scheduling Using Machine Learning.
Inventors include Ms. T Ishverya; Mr. N S S S Girish Kumar; Dr. R Karthikeyan; Dr. Ramachandro Majji; Dr. Prakash Kumar Sarangi; and Mr. Ramachandra Rao Moka.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: ABSTRACT A System and Method for Intelligent Cloud Resource Allocation and Energy-Efficient Workload Scheduling Using Machine Learning This disclosure provides a system and method for autonomous cloud resource allocation and energy-efficient workload scheduling using digital twin based predictive analytics, workload DNA profiling, carbon-aware orchestration, and explainable machine learning. The system includes a workload acquisition module, a workload DNA profiling engine, a hardware- integrated resource telemetry controller, a digital twin simulation module, a carbon-aware scheduling intelligence module, a machine learning optimization framework, a quantum-inspired multi-objective optimization module, an explainable scheduling decision engine, and a multi-cloud resource allocation controller. The system collects real-time infrastructure telemetry information, generates workload behavioral profiles, forecasts future infrastructure states through digital twin simulations, evaluates carbon emission and renewable energy parameters, and optimizes workload placement using federated learning, reinforcement learning and quantum- inspired optimization techniques. It further provides explainable scheduling recommendations and self-healing orchestration for autonomous anomaly management. The disclosed invention improves energy efficiency, reduces carbon emissions, improves infrastructure reliability, optimizes resource utilization and supports sustainable cloud computing operations.
Disclaimer: Curated by HT Syndication.
