Logical Rule Parallelization via Dependency Analysis and Resource Assignment
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Solution Overview
Problem
Existing rapid application development (RAD) suites and business rules engines execute logical blocks of execution sequentially, despite many being independent, leading to suboptimal performance.
Innovation Solution
Automatically identify independent logical blocks of execution and assign them to separate computing resources for parallel processing, utilizing an assignment service to optimize workload distribution across computing devices or resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If logical blocks are executed sequentially in RAD suites, then the system maintains simple execution flow and ease of operation, but processing speed and productivity deteriorate
Solution Approach 1:
The patent segments the sequential execution flow into independent logical blocks that can be executed in parallel. Each logical block is identified and separated based on dependency analysis, allowing independent execution while maintaining overall workflow integrity. This segmentation enables multiple blocks to run simultaneously on different computing resources, directly improving processing speed without requiring complete restructuring of the execution model.
Solution Approach 2:
The execution model transitions from static sequential ordering to dynamic parallel execution. The system dynamically determines which logical blocks can be executed in parallel by analyzing dependencies at runtime, assigning them to appropriate computing resources. This dynamic approach allows the system to optimize execution flow based on actual block independence, improving productivity while managing complexity through automated dependency tracking.
2Productivity
If independent logical blocks are executed in parallel on separate computing resources, then processing efficiency improves, but system complexity and resource management difficulty increase
Solution Approach 1:
The patent introduces an assignment service as an intermediary component that manages the complexity of parallel execution. This service acts as a mediator between the logical blocks and computing resources, automatically analyzing dependencies, determining parallel execution opportunities, and assigning blocks to appropriate resources. By centralizing this management function, the system achieves improved execution efficiency without burdening the overall system architecture with distributed complexity.
Solution Approach 2:
The system implements feedback mechanisms where the assignment service continuously monitors execution status, resource availability, and dependency satisfaction. Based on this feedback, the service dynamically adjusts the assignment of logical blocks to computing resources, optimizing execution efficiency while managing complexity through adaptive resource allocation. This feedback loop ensures that parallel execution proceeds smoothly without requiring manual intervention or complex pre-planning.
3Loss of time
If all logical blocks are assigned to the same computing resource, then resource management is simplified, but execution time increases due to sequential processing
Solution Approach 1:
The patent transitions from single-dimension sequential execution to multi-dimensional parallel execution by utilizing multiple computing resources simultaneously. Independent logical blocks are distributed across different computing resources, effectively adding a spatial dimension to the execution model. This dimensional change allows simultaneous execution of multiple blocks, dramatically reducing execution time while the assignment service manages the distribution complexity automatically.
Data Source
AI summary
Disclosed are various embodiments for automated parallelization of logical rules. A first computing device can determine individual dependencies between individual ones of a plurality of objects stored in the memory, each of the objects comprising a node representing a logical rule and at least one edge representing variable linked to the logical rule. The first computing device can then divide the plurality of objects into a plurality of groups of objects based at least in part on the individual dependencies between the individual ones of the objects, wherein individual objects within individual ones of the groups of objects are independent of individual objects within other ones of the groups of objects. Subsequently, the first computing device can assign individual ones of the groups of objects to individual computing devices for execution in parallel, the individual computing devices being separate from the first computing device.