MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202641091435 A) filed by Pragati Engineering College on July 28, 2026, for A System And Method For Intelligent Cloud Resource Allocation And Workload Optimization.
Inventors include Ms. P. Varalakshmi; Ms. P Pushpa Latha; Pemmanaboyina Chandini; Vyshnavika Burlu; and Pentakota Chandra Sekhar.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: ABSTRACT A System and Method for Intelligent Cloud Resource Allocation and Workload Optimization The present disclosure is directed to an intelligent cloud resource allocation and multi-dimensional workload optimization system and method by using adaptive infrastructure intelligence The system collects multi- dimensional infrastructure state information, including processor utilization, cache occupancy, memory locality, storage performance, network conditions, accelerator availability, thermal characteristics, power consumption and hardware reliability indicators. An adaptive workload fingerprint is formed by analyzing workload execution characteristics and resource dependencies. The system computes infrastructure compatibility scores to identify an optimal execution environment, performs dynamic resource fragmentation analysis, predicts resource contention, and orchestrates resource allocation across compute, memory, storage, networking, virtualization, and accelerator layers. The system also evaluates the need for workload migration based on execution benefit, performs reliability-aware and energy- aware scheduling, and continuously monitors the execution of workloads. We store the runtime feedback in an autonomous learning repository which improves the future allocation strategies with a closed-loop feedback controller. The invention disclosed herein enhances infrastructure utilization, workload execution efficiency, scalability, operational reliability, fault tolerance and energy efficiency while minimizing resource contention and unnecessary workload migration.
Disclaimer: Curated by HT Syndication.
