Possible Value Ranges for Concurrent Incremental Data Processing
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Solution Overview
Problem
In computing environments, existing systems face challenges in concurrently processing multiple incremental changes to data while ensuring that these changes do not exceed predefined thresholds, leading to uncertainty in determining whether a combination of pending transactions can pass a threshold, which affects resource utilization and data integrity.
Innovation Solution
The implementation of a system that uses possible value ranges (PVRs) to track the boundaries of data fields, allowing for the concurrent processing of delta transactions while enforcing thresholds by determining whether incremental changes, combined with other pending requests, can pass defined thresholds, thereby managing resource utilization effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple incremental changes are processed concurrently to improve processing efficiency, then productivity increases, but it becomes difficult to determine whether the combination of pending transactions can pass thresholds, worsening reliability
Solution Approach 1:
The system performs preliminary actions by computing possible value ranges (PVRs) for data fields before actually applying incremental changes. By calculating the minimum and maximum possible values that could result from combinations of pending transactions, the system can determine in advance whether thresholds will be violated, allowing concurrent processing to proceed safely without compromising threshold enforcement accuracy.
Solution Approach 2:
The patent introduces possible value ranges (PVRs) as an intermediary mechanism between concurrent transactions and threshold enforcement. The PVR acts as a mediator that captures the uncertainty of pending transactions while providing a deterministic way to check threshold compliance. This intermediary layer allows the system to maintain both concurrent processing efficiency and reliable threshold enforcement.
2Reliability
If the system tracks all pending transactions to ensure threshold compliance, then data integrity is maintained, but the complexity of managing and evaluating combinations of transactions increases
Solution Approach 1:
The system computes possible value ranges in advance by analyzing the minimum and maximum impacts of pending transactions on data fields. This preliminary computation consolidates multiple transaction effects into a single PVR, eliminating the need to evaluate all possible combinations of transactions while still ensuring threshold compliance and maintaining data integrity.
Solution Approach 2:
The patent transforms the complex state of multiple pending transactions into a simplified parameter representation (PVR with min and max values). By changing the representation from individual transaction details to aggregated value ranges, the system reduces management complexity while preserving the information needed for threshold enforcement and data integrity verification.
3Measurement precision
If the system evaluates all combinations of pending transactions to determine threshold compliance, then measurement precision improves, but the time required for evaluation increases
Solution Approach 1:
The system performs preliminary evaluation by computing possible value ranges that encompass all potential outcomes of pending transactions. This single PVR computation provides precise threshold compliance determination without requiring exhaustive evaluation of all transaction combinations, significantly reducing evaluation time while maintaining measurement precision.
Solution Approach 2:
Instead of evaluating all possible transaction combinations (excessive action), the system computes a single PVR that partially represents the combined effect of all pending transactions. This partial action approach provides sufficient information for accurate threshold compliance determination while avoiding the time cost of complete enumeration.
Data Source
AI summary
Embodiments of the invention relate generally to incremental computing. Specifically, embodiments of the invention include systems and methods that provide for the concurrent processing of multiple, incremental changes to a data value while at the same time monitoring and/or enforcing threshold values for that data value. For example, a method is provided that determines whether multiple incremental changes to a data field could pass a threshold based on keeping track of a possible value range for the data field.