Huawei technologies co., ltd. (20240118930). RESOURCE CONFIGURATION METHOD, APPARATUS, STORAGE MEDIUM, AND COMPUTING SYSTEM simplified abstract
Contents
- 1 RESOURCE CONFIGURATION METHOD, APPARATUS, STORAGE MEDIUM, AND COMPUTING SYSTEM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 RESOURCE CONFIGURATION METHOD, APPARATUS, STORAGE MEDIUM, AND COMPUTING SYSTEM - 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
RESOURCE CONFIGURATION METHOD, APPARATUS, STORAGE MEDIUM, AND COMPUTING SYSTEM
Organization Name
Inventor(s)
Lingchuan Sun of Shenzhen (CN)
RESOURCE CONFIGURATION METHOD, APPARATUS, STORAGE MEDIUM, AND COMPUTING SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240118930 titled 'RESOURCE CONFIGURATION METHOD, APPARATUS, STORAGE MEDIUM, AND COMPUTING SYSTEM
Simplified Explanation
The patent application abstract describes a method for determining the configuration of a computing node within a computing cluster based on the execution characteristic parameter of an application and a load model.
- The method involves obtaining the execution characteristic parameter of an application.
- Based on the execution characteristic parameter and a load model, running time periods of the application on different computing nodes with varying configurations are determined.
- According to a preset policy, the configuration of a computing node that will execute the application is then determined.
Potential Applications
This technology could be applied in cloud computing environments to optimize the performance and resource allocation of applications running on computing clusters.
Problems Solved
1. Efficient resource utilization: By determining the optimal configuration of computing nodes based on application characteristics, resource allocation can be optimized. 2. Performance improvement: Matching applications with the most suitable computing nodes can enhance overall performance and reduce execution times.
Benefits
1. Improved efficiency: By selecting the most appropriate computing node configuration, overall system efficiency can be enhanced. 2. Cost savings: Optimizing resource allocation can lead to cost savings by reducing unnecessary resource usage.
Potential Commercial Applications
Optimizing resource allocation in cloud computing environments, improving application performance, and reducing operational costs.
Possible Prior Art
Prior art may include similar methods for optimizing resource allocation in computing clusters based on application characteristics and load models.
Unanswered Questions
How does this method handle dynamic changes in application characteristics during runtime?
The method described in the abstract focuses on determining the configuration of a computing node based on the initial execution characteristic parameter of an application. It does not address how dynamic changes in application characteristics during runtime are handled.
What impact does the preset policy have on the overall performance of the system?
The abstract mentions determining the configuration of a computing node according to a preset policy. It would be interesting to understand how different preset policies could impact the overall performance and efficiency of the system.
Original Abstract Submitted
a computing cluster includes a plurality of computing nodes. a method includes: obtaining an execution characteristic parameter of an application; obtaining, based on the execution characteristic parameter of the application and a load model, running time periods of the application when the application runs on different computing nodes, where the different computing nodes have different configurations; and determining, according to a preset policy, a configuration of a computing node that executes the application.
