18544984. TECHNIQUES FOR ADAPTIVELY ALLOCATING RESOURCES IN A CLOUD-COMPUTING ENVIRONMENT simplified abstract (Microsoft Technology Licensing, LLC)
Contents
- 1 TECHNIQUES FOR ADAPTIVELY ALLOCATING RESOURCES IN A CLOUD-COMPUTING ENVIRONMENT
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 TECHNIQUES FOR ADAPTIVELY ALLOCATING RESOURCES IN A CLOUD-COMPUTING ENVIRONMENT - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
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 18544984 titled 'TECHNIQUES FOR ADAPTIVELY ALLOCATING RESOURCES IN A CLOUD-COMPUTING ENVIRONMENT
Simplified Explanation
The patent application describes a method for monitoring performance metrics of workloads in a cloud-computing environment and reallocating compute resources based on the monitoring. This can involve migrating workloads among nodes, reallocating hardware accelerator resources, adjusting transmit power for vRAN workloads, and more.
- Monitoring performance metrics of workloads in a cloud-computing environment
- Reallocating compute resources based on the monitoring
- Migrating workloads among nodes or other resources
- Reallocating hardware accelerator resources
- Adjusting transmit power for vRAN workloads
Potential Applications
This technology could be applied in various industries such as telecommunications, e-commerce, and healthcare to optimize resource allocation in cloud computing environments.
Problems Solved
This technology helps in efficiently managing workloads in a cloud-computing environment, ensuring optimal performance and resource utilization.
Benefits
The benefits of this technology include improved performance, resource efficiency, and cost-effectiveness in cloud computing environments.
Potential Commercial Applications
"Optimizing Resource Allocation in Cloud Computing Environments" - This technology could be used by cloud service providers, data centers, and enterprises to enhance the efficiency of their operations.
Possible Prior Art
There may be prior art related to workload monitoring and resource allocation in cloud computing environments, but specific examples are not provided in this context.
Unanswered Questions
How does this technology impact energy consumption in cloud computing environments?
This article does not delve into the potential impact of this technology on energy consumption within cloud computing environments. Further research may be needed to explore this aspect.
What are the potential security implications of reallocating compute resources in a cloud-computing environment?
The article does not address the security implications of reallocating compute resources in a cloud-computing environment. It would be important to investigate how this process could affect the security of the system and data stored within it.
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.
