Network Connectivity Inference with Conflict Resolution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current network analysis techniques face challenges in inferring complete connectivity among devices due to incomplete and conflicting data from different sources, requiring substantial human intervention and failing to resolve conflicts effectively.
Innovation Solution
A system and method that integrates connectivity information from various inference techniques, consolidating data at a base level to resolve conflicts and overlay higher-level connectivity information, assuming lower-level details are more accurate, to create a comprehensive network model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If connectivity information is collected from multiple inference techniques, then the completeness of network connectivity data is improved, but the complexity of processing and resolving conflicting information increases
Solution Approach 1:
The patent segments the connectivity inference process into multiple independent inference techniques (e.g., neighbor discovery, routing table analysis, ARP table analysis) that operate separately on different data sources. Each technique processes its specific data type independently, and the results are later integrated through a consolidation process that handles conflicts systematically.
Solution Approach 2:
The patent introduces an intermediary consolidation process that acts as a mediator between the multiple inference techniques and the final network connectivity model. This intermediary layer processes and resolves conflicts between different inference results, preventing direct complexity propagation to the final model while ensuring data completeness.
2Measurement precision
If human intervention is used to verify and resolve conflicts in network data, then the accuracy of connectivity inference is improved, but the time required for network analysis increases
Solution Approach 1:
The patent implements self-service conflict resolution where the system automatically verifies and resolves conflicts between different inference techniques without requiring human intervention. The consolidation process autonomously processes conflicting information, applies resolution rules, and produces accurate connectivity models independently.
Solution Approach 2:
The patent incorporates feedback mechanisms where the consolidation process continuously refines the network connectivity model by comparing results from multiple inference techniques and adjusting the model based on consistency checks. This iterative feedback process improves accuracy while maintaining automated operation.
3Measurement precision
If detailed connectivity information is collected from all network devices, then the precision of network modeling is improved, but the amount of data processing required increases
Solution Approach 1:
The patent applies local quality by collecting and processing connectivity information specifically tailored to each network device's role and characteristics. Different inference techniques focus on different aspects of connectivity relevant to specific device types (e.g., routing tables for routers, ARP tables for end devices), processing only the necessary data for each local context rather than uniformly processing all data.
Solution Approach 2:
The patent employs partial action by selectively applying different inference techniques to different parts of the network based on their specific characteristics and the level of detail required. Not all devices require the same level of analysis, so the system applies detailed processing only where necessary while using simpler methods where appropriate.
Data Source
AI summary
The connectivity information provided by a variety of inference engines is integrated to provide a set of inferred links within a network. A consolidation is performed among inference engines that operate at a base level of connectivity detail to create a model of the network at this base level. The connectivity information provided by inference engines at each subsequent higher level of connectivity abstraction is then overlaid on the base level connectivity. By separately consolidating the connectivity information at each level of abstraction, the rules for dealing with conflicts can be simplified and/or better focused to resolve the conflict. By assuming that the more detailed lower level information is likely to be more accurate, rules can be developed to modify the connectivity models produced by the higher level techniques to conform to the lower level connectivity details while still maintaining the integrity of the higher level connectivity models.