Hardware Component Classification for Automated Software Deployment
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Solution Overview
Problem
The existing methods for installing system software on computing devices within a networked environment, such as data centers, are inefficient due to the time-consuming process of determining and deploying the appropriate software for each device's unique hardware configuration, especially in large-scale setups.
Innovation Solution
A system classification model, trained on hardware configuration information and corresponding reference system software, is used to classify computing devices and identify the necessary system software for installation, utilizing machine learning and a client-server environment like Preboot eXecution Environment (PXE) to streamline the process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual methods are used to determine and deploy system software for each computing device, then software can be installed on hardware configurations, but the process is time-consuming and inefficient especially in large-scale data center environments
Solution Approach 1:
The system performs preliminary classification of computing devices into hardware types before software deployment. By pre-defining hardware type categories and classification rules, the system prepares the groundwork for rapid software matching, eliminating the need for manual assessment during the deployment process itself.
Solution Approach 2:
The patent introduces an intermediary classification system that acts as a mediator between hardware configuration and software deployment. This intermediary layer automatically categorizes devices based on hardware attributes and matches them with appropriate software, reducing direct human intervention and accelerating the deployment process.
2Measurement precision
If detailed hardware configuration analysis is performed for each device, then accurate software matching can be achieved, but the complexity of the deployment process increases
Solution Approach 1:
The patent segments the hardware configuration analysis into distinct categories such as processor type, memory capacity, storage configuration, and network interface. Each category is evaluated independently using predefined criteria, making the complex analysis process more manageable and systematic while maintaining accuracy.
Solution Approach 2:
The system transforms detailed hardware configuration parameters into simplified hardware type classifications. By changing the parameter representation from raw hardware specifications to categorized hardware types, the system maintains classification accuracy while reducing process complexity.
Data Source
AI summary
Approaches for classifying hardware components of a computing device using a classification system are described. In an example, by the classification system, a hardware configuration information of the computing device installed within a networked environment is obtained. The hardware configuration information may thus be processed based on a system classification model. The system classification model is to classify hardware components of the computing device as one of a plurality of hardware types. Once the hardware components are classified, a category of the computing device is determined. Based on the determined category, a target system software is identified and installed onto the computing device.