Microsoft technology licensing, llc (20240214871). TECHNIQUES FOR ADAPTIVELY ALLOCATING RESOURCES IN A CLOUD-COMPUTING ENVIRONMENT simplified abstract
Contents
TECHNIQUES FOR ADAPTIVELY ALLOCATING RESOURCES IN A CLOUD-COMPUTING ENVIRONMENT
Organization Name
microsoft technology licensing, llc
Inventor(s)
Bozidar Radunovic of Cambridge (GB)
Sanjeev Mehrotra of Kirkland WA (US)
Yongguang Zhang of Redmond WA (US)
Paramvir Bahl of Bellevue WA (US)
Xenofon Foukas of Cambridge (GB)
TECHNIQUES FOR ADAPTIVELY ALLOCATING RESOURCES IN A CLOUD-COMPUTING ENVIRONMENT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240214871 titled 'TECHNIQUES FOR ADAPTIVELY ALLOCATING RESOURCES IN A CLOUD-COMPUTING ENVIRONMENT
Simplified Explanation: The patent application discusses monitoring performance metrics of workloads in a cloud-computing environment and reallocating compute resources based on the monitoring.
- Reallocation of compute resources may involve migrating workloads among nodes or other resources in the cloud-computing environment.
- Reallocation can also include reallocating hardware accelerator resources and adjusting transmit power for virtual radio access network (vran) workloads.
Key Features and Innovation:
- Monitoring performance metrics of workloads in a cloud-computing environment.
- Reallocating compute resources based on the monitoring data.
- Migrating workloads among nodes or other resources.
- Reallocating hardware accelerator resources.
- Adjusting transmit power for virtual radio access network (vran) workloads.
Potential Applications: This technology can be applied in various cloud computing environments to optimize resource allocation and improve overall performance.
Problems Solved: The technology addresses the challenges of efficiently managing compute resources in dynamic cloud environments to ensure optimal performance.
Benefits:
- Improved performance of workloads.
- Efficient resource allocation.
- Enhanced scalability and flexibility in cloud computing environments.
Commercial Applications: Optimizing resource allocation in cloud computing environments can benefit cloud service providers, data centers, and businesses relying on cloud infrastructure for their operations.
Prior Art: Readers can explore prior art related to cloud resource management, workload monitoring, and resource reallocation in cloud computing environments.
Frequently Updated Research: Stay informed about the latest research on cloud resource management, workload optimization, and performance monitoring in cloud computing environments.
Questions about Cloud Resource Management: 1. How does this technology impact the efficiency of resource allocation in cloud computing? 2. What are the potential cost-saving benefits of reallocating compute resources in a cloud environment?
Original Abstract Submitted
described are examples for monitoring performance metrics of one or more workloads in a cloud-computing environment and reallocating compute resources based on the monitoring. reallocating compute resources can include migrating workloads among nodes or other resources in the cloud-computing environment, reallocating hardware accelerator resources, adjusting transmit power for virtual radio access network (vran) workloads, and/or the like.
