Network Dependency Mapping via Self-Organizing Nodes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional application dependency mapping in computer networks is often manual, prone to errors, labor-intensive, and outdated, and network-scanning approaches burden the network, leading to inaccurate maps and performance issues.
Innovation Solution
A method involving a linear communication orbit where nodes self-organize and perform mapping operations, receiving application definitions and map requests to identify and respond with metadata, enabling accurate and efficient network mapping without overloading the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network-scanning software tools are used to collect data, then mapping coverage is improved, but network performance deteriorates due to significant load
Solution Approach 1:
Nodes in the network autonomously generate and share their own connection data without requiring external scanning. Each node maintains a local data structure representing its connections and directly contributes this information to the mapping system, eliminating the need for resource-intensive network scanning while maintaining comprehensive mapping coverage.
Solution Approach 2:
The patent extracts the data collection function from centralized network scanning tools and distributes it to individual network nodes. Each node independently provides its connection information, removing the burden of network-wide scanning while preserving the ability to collect comprehensive mapping data.
2Measurement precision
If manual mapping is performed by application owners, then mapping accuracy is improved, but labor intensity increases
Solution Approach 1:
The system automatically collects mapping data from network nodes without requiring manual intervention. Nodes autonomously generate connection data, and the system automatically processes this information to create and update dependency maps, eliminating the need for manual mapping while maintaining accuracy through automated data collection from actual network connections.
Solution Approach 2:
The patent replaces the mechanical process of manual mapping with an automated electronic system. Instead of humans manually creating maps, the system electronically collects connection data from nodes and automatically generates dependency maps, significantly reducing labor intensity while maintaining or improving accuracy.
3Productivity
If network scans are scheduled during low usage periods, then network performance is improved, but data representativeness deteriorates
Solution Approach 1:
The system continuously collects connection data from network nodes in real-time as connections occur, rather than performing periodic scans. This continuous data collection ensures that the mapping information always reflects current network conditions and is representative of actual usage patterns, regardless of when data collection occurs.
Solution Approach 2:
Nodes continuously report their connection status and changes as they occur, providing real-time data that accurately represents current network conditions. This eliminates the need to schedule scans during specific periods, as data collection happens continuously and naturally reflects actual network usage.
Data Source
AI summary
This application is directed to a mapping method performed at a computational machine in a linear communication orbit. The computational machine receives an application definition the linear communication orbit. The application definition specifies criteria for establishing whether the computational machine executes a specified application, a component of the specified application, or communicate with another node executing the specified application or a component of the specified application. While a plurality of events are occurring locally at the computational machine, the computational machine identifies one or more operations meeting the application definition in real-time. The identified one or more operations meeting the application definition, and associated metadata are stored in a local mapping database of the computational machine and returned to the server system through the linear communication orbit in response to a map request received through the linear communication orbit.