Scheduled Job Execution Delay via User Notification Feedback
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Solution Overview
Problem
Current systems for executing scheduled jobs, or batch processes, face inefficiencies and resource waste due to data integrity issues and lack of flexibility in timing adjustments, especially in multi-processing environments where errors can cause disruptions and require manual override for temporary delays or cancellations.
Innovation Solution
A system that notifies end users prior to scheduled job execution, allowing temporary delays by resetting execution times based on user input, using a processing device that monitors and manages job execution times in relation to predefined notification times, enabling informed decision-making and resource optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If scheduled jobs are executed at predetermined times without manual intervention, then system automation and productivity are improved, but data integrity errors and resource waste increase due to inability to temporarily delay execution
Solution Approach 1:
The system sends notifications to users before scheduled job execution and receives feedback regarding whether to proceed or delay. This feedback mechanism allows the system to adjust execution timing based on data readiness status, preventing execution with incomplete or erroneous data while maintaining automated scheduling for jobs that are ready to run.
Solution Approach 2:
The job execution timing is made dynamic rather than fixed. The system can temporarily delay job execution based on real-time conditions (data availability) while maintaining the original scheduled time as the default. This dynamic adjustment resolves the contradiction by allowing automation to operate reliably when data is ready while providing flexibility when data integrity issues arise.
2Reliability
If manual override is allowed to delay or cancel scheduled jobs, then data integrity is improved, but system complexity and operational difficulty increase due to multiple navigation levels required
Solution Approach 1:
The notification system serves as an intermediary between the automated scheduling system and the user. Instead of requiring direct manual intervention in complex scheduling interfaces, the system communicates job status and delay requests through standardized notification channels (email, SMS, etc.), simplifying the interaction while maintaining data integrity controls.
Solution Approach 2:
The system enables users to self-manage job execution timing by allowing them to respond to notifications with simple delay requests. Users can independently delay or cancel jobs based on data readiness without requiring system administrator intervention or navigation through complex hierarchical interfaces, improving ease of operation while maintaining reliability.
3Adaptability or versatility
If scheduled jobs are permanently reset to new execution times, then flexibility is improved, but productivity decreases due to loss of original scheduling and requirement to re-reset after execution
Solution Approach 1:
The system changes the execution time parameter temporarily rather than permanently. When a user requests a delay, the system modifies the execution time parameter for that specific instance only, allowing flexibility to adapt to data readiness while preserving the original scheduled time for future reference and automatic restoration after job completion or cancellation.
Solution Approach 2:
The system performs preliminary notification and confirmation actions before permanently altering job schedules. By notifying users in advance and obtaining confirmation for delays, the system maintains productivity by ensuring that permanent schedule changes only occur when necessary and approved, while still providing the flexibility of temporary adjustments when needed.
4Use of energy by moving object
If batch processes run during off-peak hours to optimize resource usage, then energy efficiency is improved, but time sensitivity worsens due to delays in processing time-critical data
Solution Approach 1:
The system dynamically adjusts job execution timing based on data readiness rather than rigidly adhering to off-peak hour schedules. When data is ready earlier than expected, jobs can execute earlier even during peak hours. When data is not ready by the scheduled off-peak time, the system delays execution until data is available, optimizing the balance between resource efficiency and time sensitivity.
Solution Approach 2:
The notification system provides feedback to users about job execution timing and data readiness status. This enables real-time decision-making about whether to execute jobs during off-peak hours as scheduled or to delay/advance execution based on actual data availability, allowing flexible optimization of both energy efficiency and time sensitivity.
Data Source
AI summary
The present invention provides for the adjustment of the timing of a scheduled job including determining when the execution time of a scheduled job is within a predetermined time period. Prior to this time, a job execution notification is generated and submitted to an end user. The notification includes a request for time delay in the event the job should not be executed on the time noted. If the job should be delayed, a user may submit a delay request including a time delay. Upon receipt, an internal timing parameter is temporarily reset based on the delay request. The job is then automatically rescheduled for the prescribed time. If no other delay is incurred, once the job is executed, the internal timing parameter is then reset to its original time value.