Network Difference Reporting System for Hierarchical Change Detection
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Solution Overview
Problem
Network managers face challenges in efficiently identifying and reporting changes within complex networks due to the cumbersome nature of conventional text-based comparison methods, which often obscure significant changes among minor or cosmetic alterations, and lack context, making it difficult to diagnose issues effectively.
Innovation Solution
A system that categorizes network differences by locating corresponding equipment and comparing attributes hierarchically, allowing users to identify uninteresting objects and attributes, and presenting differences in organized formats such as tabular and graphic reports to facilitate rapid understanding, focusing on additions, deletions, and changes within the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional text-based comparison programs are used to compare network descriptions, then the comparison process can be automated, but the significant changes are obscured among numerous cosmetic or incidental changes
Solution Approach 1:
The patent applies local quality by differentiating the treatment of different types of changes in the network description. Cosmetic changes (like formatting or non-functional attributes) are treated differently from significant functional changes. The system identifies and categorizes changes based on their nature and impact, applying different highlighting or reporting strategies to different locations in the comparison output, thereby making significant changes stand out while minimizing noise from incidental changes.
Solution Approach 2:
The patent segments the network description comparison into distinct categories: cosmetic changes, functional changes, significant changes, and incidental changes. By dividing the comparison results into these segments, the system allows network managers to focus on specific types of changes relevant to their needs, preventing significant changes from being lost in the overall comparison output.
2Measurement precision
If text-based comparison highlights all changed lines, then completeness of change detection is achieved, but the context of changes is lost and diagnostic understanding becomes difficult
Solution Approach 1:
The patent implements nesting by organizing comparison results in a hierarchical structure where individual changed elements are nested within their parent network objects and contextual groups. Each change is presented within the context of the object it modifies, which is in turn nested within broader network configurations. This nested presentation maintains complete change detection while preserving contextual relationships, allowing diagnosticians to understand both the specific change and its broader impact.
Solution Approach 2:
The patent introduces an intermediary layer between the raw comparison data and the final presentation. This intermediary processing layer analyzes the comparison results, identifies contextual relationships, and reorganizes the data to preserve meaning. The intermediary ensures that all changes are detected while simultaneously maintaining the contextual framework necessary for diagnostic understanding.
3Measurement precision
If hundreds of pages of network description are reviewed for changes, then comprehensive analysis is possible, but the time and effort required becomes prohibitively large
Solution Approach 1:
The patent applies partial action by allowing network managers to perform comparisons at different levels of detail based on their specific needs. Rather than always analyzing every single change in full detail, the system enables selective review of specific change categories or network segments. This partial analysis approach maintains comprehensive detection capability while significantly reducing the time required for routine diagnostics by focusing effort only where necessary.
Data Source
AI summary
A network difference reporting method and system categorizes the differences between two networks, and provides an output report structured by these categories. The preferred categories include objects common to both networks that have different attributes; objects found only in the first network; objects found only in the second network; and objects common to both networks that have similar attributes. A user-interface is provided to allow a user to identify objects or attributes that are to be included or excluded from the identified differences. Preferably, the output reports includes a graphic display of differences that uses the same hierarchical object attribute structure as the networks, to facilitate a rapid understanding of the reported differences between the networks.