Network Topology Reconciliation via Contextual Data Agents
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Solution Overview
Problem
Modern computer networks face challenges in providing a comprehensive view of network topologies due to tools having different perspectives and limited discovery of related entities, leading to incomplete information for users.
Innovation Solution
A system that generates an extended network topology by reconciling a known topology with contextual topologies from multiple monitoring tools, using data source agents to integrate and provide additional relevant information while maintaining the context of user-defined entities, thereby enhancing the understanding of network entities and relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple monitoring tools are used to observe network entities, then the coverage and perspectives of network monitoring are improved, but the complexity of integrating and reconciling different tool views increases
Solution Approach 1:
The system segments the network monitoring task by assigning different monitoring tools to observe specific entities or aspects of the network. Each tool maintains its own contextual topology view, and the reconciliation process segments the integration work by processing relationships in manageable units rather than attempting to reconcile all tool views simultaneously.
Solution Approach 2:
The patent introduces a topology reconciliation mechanism that acts as an intermediary between multiple monitoring tools. This intermediary receives contextual topologies from various tools, processes their relationships, and produces a unified extended topology, thereby simplifying the integration complexity by centralizing the reconciliation function.
2Measurement precision
If monitoring tools focus on specific entities and relationships, then the depth of monitoring for those entities is improved, but the overall network topology view becomes incomplete
Solution Approach 1:
The system merges the individual contextual topologies from multiple monitoring tools into a unified extended topology. By combining the detailed views from each tool while preserving their specific entity relationships, the system achieves both deep monitoring of specific entities and a complete overall network topology view.
Solution Approach 2:
The patent extends the topology by adding another dimension to the monitoring view. Instead of relying on a single flat topology view, the system creates an extended topology that incorporates additional entities and relationships discovered by different tools, effectively adding depth and breadth to the network observation without losing the precision of individual tool views.
3Ease of operation
If monitoring tools operate independently with their own views, then the operational simplicity of individual tools is maintained, but the collaborative value and information sharing between tools is reduced
Solution Approach 1:
The system implements a universal topology reconciliation mechanism that can process and integrate views from multiple different monitoring tools simultaneously. This multi-functional approach allows each tool to continue operating independently with its own simple interface, while the reconciliation system universally handles the integration, enabling information sharing without complicating individual tool operations.
4Loss of information
If the system integrates data from multiple monitoring tools, then the comprehensiveness of network topology information is improved, but the processing time and computational resources required increase
Solution Approach 1:
The system performs preliminary actions by having monitoring tools pre-establish their contextual topologies and entity relationships before the reconciliation process. This preliminary preparation allows the topology reconciliation mechanism to work with pre-processed data structures, reducing the computational burden and time required during the actual integration phase while maintaining comprehensive topology information.
Data Source
AI summary
In embodiments, a known network relation is generated from a known topology of a network and is sent to a first data source agent associated with a first tool configured to monitor the network. A first contextual topology of the network is received from the first data source agent and is based on the known network relation and first data associated with the first tool. An extended topology is generated by reconciling the known topology with at least the first contextual topology. In further embodiments, a derived network relation is received from the first data source agent. The derived network relation is sent to a second data source agent. Second contextual topology based, at least in part, on the derived network relation can be received from the second data source agent. An updated extended topology based, at least in part, on the second contextual topology can be generated.