Unified Network Graph Modeling for Explicit and Implicit Entities
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Solution Overview
Problem
Current network analysis systems fail to provide a unified, comprehensive view of computing environments that include both explicit and implicit network components, particularly in large-scale cloud deployments, leading to inefficient analysis and increased costs due to the need for separate representation of similar objects and the exclusion of implicit objects from network analysis.
Innovation Solution
A method and system for generating unified graph models that collect and genericize network entity data features to create a multi-dimensional data structure representing network entities and their relationships, including both explicit and implicit objects, enabling a unified view and efficient analysis across multiple layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If current traffic-independent solutions represent each network component separately, then comprehensive coverage of all components is achieved, but analysis efficiency decreases and costs increase
Solution Approach 1:
The patent merges multiple similar network components (firewalls, load balancers, routing devices) into unified graph model representations. By representing dissimilar objects providing similar functionalities as equivalent graph nodes with standardized attributes, the system achieves comprehensive coverage while enabling efficient batch processing and analysis through the unified graph structure.
Solution Approach 2:
The unified graph model provides a universal representation framework that can handle multiple types of network components (explicit and implicit objects) through a common data structure. This universal model enables the same analysis processes to be applied across diverse network entities, improving productivity while maintaining comprehensive coverage.
2Ease of operation
If traffic-independent solutions analyze only explicit network objects, then analysis simplicity is maintained, but implicit objects are excluded from network analysis
Solution Approach 1:
The unified graph model acts as an intermediary layer between explicit network objects and implicit objects. By representing both types of objects within the same graph structure using standardized node types and relationships, the system maintains analysis simplicity while enabling the inclusion of implicit objects that were previously excluded from network analysis.
3Measurement precision
If separate analysis is performed for each network component type, then detailed component understanding is achieved, but a unified network view is not provided
Solution Approach 1:
The patent segments the network analysis into standardized graph nodes and edges with specific attributes for detailed component understanding, while simultaneously organizing these segments into a unified graph structure. This segmentation approach allows detailed analysis of individual components through their specific attributes while maintaining the ability to perform unified network-wide analysis through graph traversal and query operations.
Solution Approach 2:
The unified graph model introduces a new dimensional organization of network data, transforming traditional flat or hierarchical component representations into a graph-based multi-dimensional structure. This enables simultaneous access to detailed component information through node attributes and unified network relationships through graph edges, providing both detailed understanding and unified view.
Data Source
AI summary
A system and method for generating unified representation models for network entities is presented. The method includes collecting network entity data feature for a network entity of a plurality of network entities, the network entity data feature including a network entity property; genericizing the network entity based on the collected network entity data feature to generate a generic network entity; identifying a functionality executing in a cloud computing environment by another entity; generating an imputed entity, wherein the imputed entity corresponds to the identified functionality; generating a network representation based on the generic network entity and the imputed entity, wherein the generated network representation is a multi-dimensional data structure representing at least the plurality of network entities and relations between the network entities of the plurality of network entities; and storing the generated network representation.