Item Re-Evaluation Scheduling for Change Detection Backlogs
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Solution Overview
Problem
Existing systems face challenges in efficiently detecting and resolving system errors and monitoring performance in real-time due to the exponential increase in latency with increasing data volumes, making it difficult to differentiate between new and existing items and causing potential financial hardship.
Innovation Solution
Items are dynamically scheduled for re-evaluation based on detected changes, with higher frequency for items showing possible changes, and using multiple item identifiers to determine if an item is new or existing, allowing for efficient processing and storage of records.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data monitoring is performed at near real-time frequency, then system error detection speed is improved, but processing time and computational resources increase exponentially with data volume
Solution Approach 1:
The patent segments the data processing task by dividing monitoring into periodic sampling intervals rather than continuous monitoring. The system processes data in discrete time windows, evaluating items at scheduled intervals based on their change probability. This segmentation reduces the computational burden while maintaining effective error detection, directly resolving the contradiction between real-time detection and processing efficiency.
2Measurement precision
If all items are evaluated frequently for changes, then detection accuracy is improved, but processing overhead increases significantly
Solution Approach 1:
The patent implements dynamic evaluation scheduling where the re-evaluation frequency of each item is adjusted based on its individual change probability. Items with higher likelihood of change are evaluated more frequently, while stable items are evaluated less often. This dynamic adaptation maintains high detection accuracy for changing items while significantly reducing processing overhead for stable items, resolving the contradiction between detection precision and energy consumption.
3Measurement precision
If multiple item identifiers are generated and compared, then accuracy in differentiating new vs. existing items is improved, but computational complexity increases
Solution Approach 1:
The patent generates multiple item identifiers (hashes) but does not require all of them to be processed equally. Instead, it uses a hierarchical comparison approach where identifiers are evaluated in sequence or selectively based on their discriminatory power. This partial processing strategy maintains high identification accuracy by using multiple identifiers when needed while avoiding the full computational complexity of processing all identifiers for every item, thus resolving the contradiction between identification precision and system complexity.
Data Source
AI summary
Embodiments are directed towards managing and tracking item identification of a plurality of items to determine if an item is a new or existing item, where an existing item has been previously processed. In some embodiments, two or more item identifiers may be generated. In one embodiment, generating the two or more item identifiers may include analyzing the item using a small item size characteristic, a compressed item, or for an identifier collision. The two or more item identifiers may be employed to determine if the item is a new or existing item. In one embodiment, the two or more item identifiers may be compared to a record about an existing item to determine if the item is a new or existing item. If the item is an existing item, then the item may be further processed to determine if the existing item has actually changed.