Network Inventory Life Cycle Tracking via Event-Driven Historical Data Capture
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Solution Overview
Problem
Conventional inventory management systems for computer networks provide only a current view of network elements, lacking historical data and life cycle information, which limits decision-making capabilities for administrators.
Innovation Solution
An inventory management system (IMS) that captures and maintains complete historical data for network elements, allowing tracking by location, time, and network changes, providing a 'cradle-to-grave' life cycle view by comparing current and stored inventory information and generating events for changes, thereby updating the database with historical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional inventory management systems only maintain current inventory data, then the system complexity is reduced and data storage requirements are minimized, but the ability to provide historical life cycle information and support informed decision-making is lost
Solution Approach 1:
The system performs preliminary actions by capturing and storing inventory data at each change event before it is lost. The event generator detects inventory changes and triggers database updates to preserve historical information proactively, ensuring complete life cycle data is available for future analysis without requiring complex real-time tracking mechanisms.
Solution Approach 2:
The system creates copies of inventory data at each state change by generating event records that capture the before and after states of inventory elements. These copied records are stored in the database as historical data, allowing the system to maintain comprehensive life cycle information without requiring the original physical inventory to be continuously monitored.
2Reliability
If the system maintains complete historical data for all network elements, then decision-making capability is improved, but data storage requirements and processing overhead increase
Solution Approach 1:
The system segments inventory data into discrete event records, where each record represents a specific change event (addition, removal, modification) of an inventory element. This segmentation allows the system to store only relevant change information rather than continuous snapshots of the entire inventory, reducing data volume while maintaining reliability for decision-making.
Solution Approach 2:
The system uses periodic event-driven updates rather than continuous monitoring. The event generator triggers database updates only when inventory changes occur, creating a periodic action pattern that captures essential historical data without generating excessive data volume. This approach maintains reliability by recording all significant events while minimizing redundant data storage.
3Ease of operation
If the system provides detailed life cycle tracking of network elements, then administrative control and visibility are enhanced, but the time required to process and analyze inventory data increases
Solution Approach 1:
The system implements self-service through automated event generation and database updating. When inventory changes occur, the event generator automatically detects the change, creates the appropriate event record, and triggers the database manager to update the historical data. This eliminates manual data entry and processing time, providing enhanced inventory visibility without increasing administrative burden.
Solution Approach 2:
The system establishes a feedback loop where inventory changes automatically trigger event generation and database updates. This feedback mechanism ensures that the database is continuously synchronized with the actual inventory state without requiring manual intervention, providing real-time visibility while minimizing processing time through automated workflows.
Data Source
AI summary
An inventory management system (IMS) is described herein that captures historical data for network elements of a computer network. The IMS maintains the historical data to provide a life cycle view of the elements as utilized within the computer network. For example, the IMS may include a network scan module that receives current inventory information from at least one of the network devices, wherein the current inventory information lists elements currently deployed within network device. An event generator compares the current inventory information with the stored inventory information. A database manager updates the database to store historical data for the network devices based on the comparison.