Batch Processing Scheduling via Resource and Regulatory Repositories
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Solution Overview
Problem
Current batch processing scheduling methods fail to optimize the timing of batch operations based on their execution constraints and the resources they consume, leading to inefficient use of infrastructure during peak and non-peak periods.
Innovation Solution
A device and method that utilize a regulatory repository and resource repository, managed through man-machine interfaces, to create and store execution rules and resource usage metrics in matrix form, allowing for the optimization of batch processing schedules by determining the optimum execution plan that reduces overall execution time and maximizes resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If batch processing operations are scheduled without optimization based on execution constraints and resource consumption, then the scheduling process is simple, but the infrastructure becomes inefficient during peak and non-peak periods
Solution Approach 1:
The patent applies preliminary action by pre-defining execution constraints and resource consumption metrics for batch processing operations before scheduling. The system stores these constraints and metrics in advance in a repository, allowing the scheduling mechanism to make informed decisions without complex real-time analysis, thus improving infrastructure efficiency while maintaining manageable complexity.
Solution Approach 2:
The patent implements dynamics by creating an adaptive scheduling mechanism that adjusts batch processing schedules based on varying infrastructure conditions. The system dynamically evaluates execution constraints and resource consumption metrics to optimize scheduling decisions during different peak and non-peak periods, transforming a static scheduling approach into a dynamic one that responds to changing conditions.
2Loss of time
If batch processing schedules are optimized based on execution constraints and resource consumption metrics, then overall execution time is reduced, but the complexity of the scheduling mechanism increases
Solution Approach 1:
The patent reduces batch processing execution time by pre-calculating and storing execution constraints and resource consumption metrics. This preliminary preparation allows the scheduling mechanism to quickly determine optimal schedules without performing complex real-time calculations, thus reducing execution time while keeping the scheduling mechanism complexity manageable through pre-computed data.
Solution Approach 2:
The patent employs feedback by using resource consumption metrics from previous batch processing executions to inform future scheduling decisions. The system continuously monitors and stores these metrics, feeding them back into the scheduling mechanism to progressively optimize execution time. This feedback loop enables the system to learn from past performance and improve scheduling efficiency over time.
3Productivity
If resource consumption metrics are measured and stored for each batch processing operation, then resource utilization is maximized, but the data collection and storage infrastructure becomes more complex
Solution Approach 1:
The patent achieves universal resource utilization by creating a multi-functional repository that stores both execution constraints and resource consumption metrics for various batch processing operations. This unified storage infrastructure serves multiple purposes: scheduling optimization, performance monitoring, and resource allocation, thereby maximizing resource utilization while avoiding the need for separate complex data collection systems for each function.
Solution Approach 2:
The patent introduces an intermediary repository structure that mediates between resource consumption measurement and scheduling optimization. This intermediary layer standardizes the collection and storage of resource metrics, simplifying the data infrastructure by providing a single point of access and management rather than requiring direct integration with multiple scheduling and monitoring systems.
Data Source
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AI summary
The present invention relates to a device comprising at least one computer machine and software for implementing a mechanism for creating schedules, batch processing, optimized for a given IT infrastructure and which consists of: - a hardware and software arrangement for storing a resource and regulatory repository, - a module for constructing an optimized execution schedule with all the elements collected by the resource repository and in compliance with the execution rules determined by the regulatory repository.