Executable Graph Ownership Overlays for Real-Time Model Boundaries
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Solution Overview
Problem
Existing system architectures that separate data storage from processing logic lead to impedance mismatches, inhibiting flexibility, extensibility, and responsiveness, particularly in time-critical applications like medical devices and autonomous vehicles.
Innovation Solution
Executable graph-based models that dynamically combine data and processing functionality at run-time while maintaining separability, with ownership overlays to manage and visualize ownership boundaries among multiple owners.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data storage is separated from processing logic, then system architecture is more organized and maintainable, but flexibility and responsiveness are inhibited
Solution Approach 1:
The patent implements an n-tier architecture where presentation layer, processing logic layer, and data access layer are nested within each other, with each layer encapsulating specific functionality. This nesting allows the system to maintain clear organizational boundaries while enabling flexible interaction between layers through standardized interfaces, resolving the contradiction between architectural organization and system flexibility.
Solution Approach 2:
The system segments functionality into distinct layers: presentation layer for UI, processing logic layer for business rules, and data access layer for data operations. Each segment operates independently with defined interfaces, allowing individual layers to be modified, replaced, or scaled without affecting others, thus maintaining both organizational clarity and adaptability.
2Ease of repair
If data storage is separated from processing logic, then system maintainability is improved, but real-time processing performance deteriorates
Solution Approach 1:
The data access layer performs preliminary data retrieval and preprocessing operations before data reaches the processing logic layer. By preparing data in advance and caching frequently accessed data in the data access layer, the system reduces real-time processing delays while maintaining the benefits of separated architecture for ease of maintenance.
Solution Approach 2:
The data access layer acts as an intermediary between the processing logic layer and data storage, optimizing data retrieval operations and reducing the time burden on the processing layer. This mediator handles data formatting, validation, and caching, thereby improving real-time performance while preserving architectural maintainability.
3Device complexity
If data and processing logic are in separate tiers, then system modularity is enhanced, but system extensibility is reduced
Solution Approach 1:
Each layer in the n-tier architecture is designed with universal interfaces that can accommodate multiple implementations. The data access layer can work with various data sources (databases, files, APIs), and the processing logic layer can handle different business rules through configurable parameters, enabling the modular system to extend easily to new functionalities without breaking existing structures.
4Reliability
If layers are physically separated, then system security is improved, but system responsiveness deteriorates
Solution Approach 1:
The data access layer maintains continuous connections to data sources and caches frequently accessed data, ensuring that data retrieval operations continue without repeated physical access to storage systems. This continuity preserves security boundaries while reducing the physical separation penalty on responsiveness, as data flows continuously through the layered architecture without repeated authentication or connection establishment overhead.
Data Source
AI summary
A method for maintaining ownership integrity of templated executable graph-based models is provided. A node template that comprises a predetermined node structure and rules governing generation of node instances is obtained. A bounded executable run-time node is generated. The bounded executable run-time node comprises the node template, a node instance, and an overlay structure. The overlay structure comprises a run-time overlay and an ownership overlay. The run-time overlay comprises an overlay template and an overlay instance that includes processing logic for interaction with the node template and/or the node instance during execution. The ownership overlay defines an ownership rule associated with the bounded executable run-time node. A stimulus and an associated context are received and, in response to the stimulus being received, execution of the processing logic of the run-time overlay is caused in accordance with the ownership rule of the ownership overlay.


