Cross-Platform Operation Validation for Feasible Task Execution
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Solution Overview
Problem
Current computing frameworks face challenges in managing the complexities of large data operations, leading to bottlenecks in data processing and storage, with a gap between code creation and execution, and a lack of effective validation of operations before execution.
Innovation Solution
A computing system performs preliminary validation of operations by checking compatibility with data constraints and contextual information, ensuring feasibility before execution, and generates detailed results to enhance operation execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current computing frameworks execute operations using libraries of code without preliminary validation, then operations can be performed quickly, but errors and infeasible operations occur frequently leading to wasted computing resources
Solution Approach 1:
The patent performs preliminary validation of operations before execution by checking compatibility between operation constraints and data characteristics. This advance validation prevents infeasible operations from consuming computing resources, directly resolving the contradiction between operational reliability and resource waste.
Solution Approach 2:
The patent introduces an intermediate validation layer between operation submission and execution. This intermediary component analyzes operation constraints, retrieves relevant data characteristics, and determines feasibility before the operation reaches the execution stage, preventing resource waste from invalid operations.
2Productivity
If distributed computing is used to handle large data sizes, then data processing capacity increases, but system complexity and operational expenses increase
Solution Approach 1:
The patent implements feedback mechanisms where validation results and operation outcomes are analyzed to improve future operation planning. The system learns from past operations to better predict feasibility and optimize resource allocation, managing complexity through intelligent feedback loops rather than brute-force distributed processing.
Solution Approach 2:
The patent dynamically adjusts operation parameters and validation thresholds based on data characteristics and system state. By changing parameters adaptively rather than using fixed complex distributed computing configurations, the system manages complexity while maintaining productivity.
3Adaptability or versatility
If code libraries are manually programmed and stored, then operations can be customized, but the process is time-consuming and error-prone
Solution Approach 1:
The patent enables the system to automatically retrieve, validate, and execute operations based on data characteristics without requiring manual programming of code libraries. The self-service mechanism reduces setup time and errors while maintaining customization through automatic operation generation and selection.
Solution Approach 2:
The patent uses templates and patterns for common operations that can be automatically instantiated and customized. Instead of manually programming each operation from scratch, the system copies and adapts proven operation patterns, reducing setup time while maintaining versatility through parameter customization.
Data Source
AI summary
Computing systems methods, and non-transitory storage media are provided for retrieving information regarding an operation to be performed by a platform, performing a preliminary validation of the operation, generating details regarding the preliminary validation, transmitting at least a subset of the details of the preliminary validation to the platform, and populating the generated details on an interface. If the preliminary validation fails, the platform refrains from performing the operation. Furthermore, the logic describing the operation can be executed on different platforms and is not bound or limited to one platform.