Tree-Structured Software Recognition for Faster Asset Matching
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Solution Overview
Problem
Current software asset management systems require excessive computational resources due to the need to test each instance of software inventory data against an entire database of known software, leading to inefficiencies as the number of devices and software variations increase.
Innovation Solution
A tree-structured database is used to organize software inventory data, allowing for efficient software identification by testing against a subset of rules based on specific properties, reducing the number of database queries and improving processing speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If each instance of software inventory data is tested against the entire database of known software, then software identification accuracy is maintained, but computational resources and processing time increase exponentially
Solution Approach 1:
The database of known software is segmented into a tree structure with multiple levels of nodes. Each node represents a subset of software applications based on shared characteristics. When identifying software, the system traverses the tree structure and only tests software inventory data against the subset of known software at each node, rather than testing against the entire database. This segmentation dramatically reduces the number of comparisons needed while maintaining identification accuracy.
2Productivity
If the database of known software is structured as a tree with multiple nodes splitting the database into subsections, then processing speed and efficiency are improved, but database structure complexity increases
Solution Approach 1:
The database is divided into a hierarchical tree structure where each node contains a subset of software applications. This segmentation allows the system to process software identification by traversing the tree and testing only the relevant subset at each level, improving processing speed while the structured organization manages the complexity through systematic categorization.
Solution Approach 2:
The database is pre-organized into the tree structure with software applications pre-categorized at different nodes based on their characteristics. This preliminary organization of data into hierarchical subsets allows for rapid retrieval and comparison during software identification, eliminating the need for exhaustive searching and significantly improving processing efficiency.
3Ease of operation
If software inventory data is collected in raw format from various devices, then data collection simplicity is maintained, but software identification effort and processing complexity increase
Solution Approach 1:
The tree-structured database acts as an intermediary between the raw software inventory data collected from devices and the identification process. The tree structure organizes and pre-processes the comparison logic, allowing the system to handle raw data efficiently by guiding the comparison process through hierarchical nodes, thereby reducing the identification effort despite the raw format of incoming data.
Data Source
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AI summary
A method for software identification in a software asset management system is provided. The method comprises receiving software inventory data from a user terminal and processing the software inventory data, wherein processing the software inventory data comprise identifying software information based on the software inventory data. Thereby the software characteristics are identified.