Job Scheduling via Resource Availability Thresholds
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Solution Overview
Problem
Conventional batch processing systems execute jobs as soon as resources become available, leading to resource contention and the need for manual intervention to manage job scheduling efficiently in computer systems.
Innovation Solution
A method and system that collect resource utilization data for system components, identify the necessary resources for a job, and determine an optimal execution time based on resource availability thresholds, reducing the need for manual intervention by scheduling jobs when sufficient resources are available.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If jobs are executed as soon as resources become available, then resource utilization is maximized, but resource contention increases and system performance deteriorates
Solution Approach 1:
The system performs preliminary analysis of resource utilization data and job requirements before execution to determine optimal scheduling times. By predicting future resource availability and analyzing historical patterns, the system schedules jobs in advance at times when resources will be available, preventing resource contention before it occurs.
Solution Approach 2:
The system continuously collects resource utilization data from system components and uses this feedback to dynamically adjust job scheduling decisions. By monitoring current and historical resource usage patterns, the system can identify optimal execution times that balance resource utilization with system performance requirements.
2Productivity
If manual intervention is used to manage job scheduling, then resource allocation can be optimized, but labor costs and operational complexity increase
Solution Approach 1:
The system automatically performs job scheduling by collecting resource utilization data, analyzing job requirements, and determining optimal execution times without human intervention. The system serves itself by making intelligent scheduling decisions based on monitored resource patterns, eliminating the need for manual schedule management while maintaining optimization.
Solution Approach 2:
The patent replaces manual mechanical scheduling operations with an automated computational system. Instead of human operators manually analyzing and scheduling jobs, the system uses automated data collection, analysis, and decision-making processes to determine job execution times, substituting human labor with computational intelligence.
3Speed
If resource allocation is determined without analysis, then job execution is faster, but resource availability thresholds are not met and contention occurs
Solution Approach 1:
The system performs preliminary analysis of resource utilization patterns and job requirements before determining execution times. By analyzing historical data and predicting future resource availability, the system identifies optimal execution moments that satisfy resource thresholds, ensuring both speed and reliability are achieved through advance planning.
Data Source
AI summary
Aspects of the present disclosure are directed toward collecting resource utilization data for a set of system components of a computing system. The resource utilization data may include performance records for a set of jobs. By analyzing the collected resource utilization data for the set of system components, a resource allocation may be identified for a particular job of the set of jobs. Aspects are also directed toward determining, based on the resource allocation for the particular job and the resource utilization data for the set of system components, a first execution time for the particular job. The first execution time may be a time when the computer system achieves a resource availability threshold with respect to the resource allocation. Aspects are also directed toward performing the particular job at the first execution time.