Graph-Based Model Contracts for Low-Latency Access Control
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Solution Overview
Problem
Existing n-tier architectures separate data storage from processing logic, leading to inefficiencies such as reduced flexibility, extensibility, and responsiveness, which are detrimental in time-critical applications like medical devices and autonomous vehicles.
Innovation Solution
An executable graph-based model integrates data and processing logic within a single model, using contracts and scopes to manage access and maintain separability, allowing dynamic combination at run-time while preserving offline separability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If data storage is separated from processing logic in n-tier architecture, then data management and processing can be independently optimized, but system flexibility, extensibility, and responsiveness are reduced
Solution Approach 1:
The patent segments the system into an executable graph-based model (containing data and associated processing logic) and a separate data access layer. This allows the graph model to be independently optimized for specific processing tasks while maintaining the ability to access underlying data storage through standardized interfaces, thus resolving the contradiction between independent optimization and system flexibility.
Solution Approach 2:
The patent introduces a data access layer as an intermediary between the executable graph-based model and the underlying data storage. This mediator enables independent optimization of each layer while maintaining seamless integration, allowing the graph model to operate with high flexibility and responsiveness without being tightly coupled to specific storage implementations.
2Device complexity
If data storage is separated from processing logic in n-tier architecture, then technical layers can use separate components, but processing delays and latency increase
Solution Approach 1:
The patent merges data and processing logic into a unified executable graph-based model, where nodes represent data elements and edges represent processing relationships. This integration eliminates the need for repeated data access operations across multiple technical layers, significantly reducing processing delays and latency while maintaining architectural structure through the graph model's organized node-edge framework.
3Productivity
If data and processing logic are integrated in executable graph-based model, then processing responsiveness is improved, but access control and data ownership management become more difficult
Solution Approach 1:
The patent applies local quality by implementing access control at the node level within the graph model. Each node can have its own access control attributes and ownership information, allowing fine-grained control over data access while maintaining the integrated structure. This enables responsive processing within the graph while managing access control complexity through localized attributes rather than global control mechanisms.
Data Source
AI summary
A method for access management in graph-based model is provided. The graph-based model comprises a plurality of nodes and an overlay structure comprising processing logic. The overlay structure is associated with one or more nodes of the plurality of nodes. Processing circuitry determines a first node group of the graph-based model. The first node group comprises at least one node. The processing circuitry associates a first contract with the first node group such that the first contract is configured to act as a proxy for one or more nodes within the first node group in relation to requests from outside the first node group. The processing circuitry receives a stimulus and a context associated therewith. The stimulus is associated with the first contract. The processing circuitry maps the stimulus to the first contract to determine an access response. The processing circuitry processes the stimulus based on the access response.