Future Dataset Transaction Scheduling for Conflict Resolution
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Solution Overview
Problem
Existing enterprise data management systems face challenges in managing conflicts arising from simultaneous requests to modify a dataset at future times, leading to inconsistencies and errors due to overlapping or conflicting modifications.
Innovation Solution
A system is developed to manage and schedule multiple requests for dataset modifications at future times, identifying conflicts, determining an execution order, and applying rules to resolve them, while generating a future state representation of the dataset for user interface display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple entities are allowed to request future modifications to the dataset independently, then the system's adaptability and entity autonomy are improved, but data consistency and conflict resolution become problematic
Solution Approach 1:
The system performs preliminary conflict detection by computing the future state of the dataset by applying scheduled modifications in temporal order before they are actually executed. This allows the system to identify conflicts in advance and resolve them by notifying entities or discarding lower-priority requests, thereby maintaining data consistency while preserving entity autonomy to request modifications
Solution Approach 2:
The system implements a feedback mechanism where conflict notifications are sent back to entities when their scheduled modifications would create conflicts. This feedback loop allows entities to be informed of potential issues and enables the system to discard lower-priority requests, thus resolving the contradiction between allowing independent modifications and maintaining data consistency
2Reliability
If the system schedules and resolves conflicts among future modifications, then data integrity is improved, but system complexity increases
Solution Approach 1:
The system segments the conflict resolution process into distinct components: (1) receiving scheduled modifications, (2) computing future state by applying modifications in temporal order, (3) detecting conflicts between modifications, (4) notifying entities of conflicts, and (5) discarding lower-priority requests. This segmentation makes the complex task of maintaining data integrity more manageable and implementable
3Measurement precision
If the system computes future state by applying scheduled modifications in temporal order, then conflict detection accuracy is improved, but processing time increases
Solution Approach 1:
The system performs the computationally intensive future state computation in advance, before actual modifications are executed. By applying modifications in temporal order and detecting conflicts preliminarily, the system ensures high conflict detection accuracy while distributing the processing load over time, reducing the impact on actual modification execution time
Data Source
AI summary
Techniques for managing requests to modify a data set at future times are disclosed. The system receives a request to modify the data set at a future time, such as in a future time window. The system generates a representation of the data set at the future time. The system determines the future state of the data set based on the current state of the data set and requested future modifications to the data set. The system determines whether a conflict exists between the request to modify the data set at the future time and another scheduled request to modify the data set at the future time. Based on determining whether a conflict exists, the system performs one or more of scheduling the request to modify the data set at the future time and performing a remediation action to address the conflict.