Actor-Driven Distributed Computational Graph for Dynamic Data Pipelines
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Solution Overview
Problem
Existing data pipelines are limited in their capabilities, being either rigidly programmed for specific tasks or restricted to linear configurations, which hinders their use in complex situations requiring branching or recurrent modifications for predictive analysis of large data sets.
Innovation Solution
An actor-driven distributed computational graph system that intelligently manages data pipelines through event-driven actor-based flows, enabling high-throughput event message handling and robust operation in a fully decoupled architecture. This system combines real-time processing of data streams with retrieval of stored data for predictive analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data pipelines are rigidly programmed for specific tasks, then reliability is improved, but adaptability deteriorates
Solution Approach 1:
The patent implements dynamic pipeline configuration where the computational graph can be modified at runtime through actor-driven events. Pipelines can be created, modified, and destroyed dynamically based on incoming data and operational requirements, resolving the contradiction between rigid programming for reliability and flexibility for adaptability.
Solution Approach 2:
The system segments the data pipeline into independent actor components that can be individually managed, created, and configured. Each actor represents a discrete transformation unit that can be dynamically assembled into different pipeline configurations, enabling both reliability through modular design and adaptability through reconfigurability.
2Device complexity
If data pipelines are configured in linear arrangement, then device complexity is reduced, but adaptability deteriorates
Solution Approach 1:
The patent transitions from one-dimensional linear pipeline arrangements to multi-dimensional computational graphs with multiple paths, cycles, and branching points. Actors can have multiple inputs and outputs, enabling complex data flow patterns while maintaining manageable complexity through the actor model and event-driven coordination.
Solution Approach 2:
Event messages serve as intermediaries between actors in the computational graph, enabling complex interactions and branching logic without requiring direct point-to-point connections. The event-driven architecture mediates the complexity of multi-path data flows while preserving the simplicity of individual actor implementations.
3Reliability
If centralized service coordinates all information exchange, then reliability is improved, but device complexity deteriorates
Solution Approach 1:
The patent extracts the coordination function from a centralized service and distributes it to individual actors that autonomously process events and manage their own state. This eliminates the single point of failure and complexity associated with centralized coordination while maintaining reliability through the consistency of the event-driven model and computational graph structure.
Data Source
AI summary
A system for dynamic predictive analysis of data sets using an actor-driven distributed computational graph, wherein a pipeline orchestrator creates and manages individual data pipelines while providing data caching to enable interactions between specific activity actors within pipelines. Each pipeline then comprises a pipeline manager that creates and manages individual activity actors and directs operations within the pipeline while reporting back to the pipeline orchestrator.