Quota Accounting Using Possible Value Ranges
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Solution Overview
Problem
Existing computing systems face challenges in concurrently processing multiple incremental changes to data while ensuring that these changes do not exceed predefined thresholds, particularly in environments where transactions can be aborted or processed in varying sequences, leading to uncertainty in determining whether a combination of pending transactions will pass a threshold.
Innovation Solution
The implementation of a system that uses possible value ranges (PVRs) to track the lowest and highest possible values of a data field, allowing it to determine whether a subset of pending transactions can cause the data field to pass a threshold by evaluating the impact of each transaction and adjusting boundaries accordingly, thereby enabling concurrent processing while enforcing threshold constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple incremental changes are processed concurrently to improve processing efficiency, then productivity increases, but the ability to accurately determine whether thresholds are exceeded deteriorates due to uncertain transaction sequences and aborts
Solution Approach 1:
The system performs preliminary actions by calculating possible value ranges (PVRs) for data fields before transactions are fully committed. By determining the minimum and maximum possible values that could result from combinations of pending transactions, the system proactively identifies whether thresholds will be exceeded, allowing for early intervention while maintaining concurrent processing.
Solution Approach 2:
The patent introduces an intermediary mechanism (PVR calculation module) that acts between the concurrent transaction processors and the threshold checking logic. This intermediary computes the range of possible outcomes without requiring sequential transaction processing, thus maintaining productivity while restoring reliable threshold determination.
2Reliability
If the system tracks all possible combinations of pending transactions to ensure accurate threshold determination, then reliability improves, but device complexity increases
Solution Approach 1:
Instead of tracking all possible transaction combinations exhaustively, the system performs partial action by calculating only the bounds (minimum and maximum) of possible value ranges. This approach provides sufficient information for threshold determination without the excessive complexity of enumerating every combination, achieving reliability with manageable system complexity.
3Measurement precision
If the system evaluates the impact of each pending transaction on possible value ranges to maintain threshold constraints, then threshold control accuracy improves, but processing time increases
Solution Approach 1:
The system changes the parameter representation from tracking individual transaction impacts to tracking aggregated possible value ranges (minimum and maximum bounds). This parameter transformation allows for precise threshold control by comparing bounds against threshold values, while reducing processing time through efficient range arithmetic operations instead of individual transaction evaluation.
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 implements domain quotas within a data storage system.