Data Request Subset Processing Under Resource Constraints
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Solution Overview
Problem
Existing systems struggle to manage data item requests efficiently when resource constraints, such as budget limits, are exceeded, leading to computational resource wastage and inefficiencies.
Innovation Solution
A computer system dynamically splits data item requests into subsets based on resource constraints, generating unique identifiers for approved and pending subsets, optimizing resource allocation and reducing computational errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system processes all requested data items, then the user receives complete data, but the resource constraint is exceeded causing computational waste
Solution Approach 1:
The system segments the requested data items into multiple subsets based on resource constraints. Each subset is processed separately, with the first subset containing items that can be fulfilled within available resources. This segmentation allows the system to provide partial results without wasting computational resources on unfulfillable requests.
Solution Approach 2:
The system applies partial action by fulfilling only the portion of the data request that can be satisfied within resource constraints. Instead of attempting to process all requested items and wasting resources on excess computations, the system processes exactly what can be delivered, indicated by the count of fulfilled items.
2Loss of energy
If the system rejects requests exceeding resource constraints, then computational resources are preserved, but the user receives incomplete or no data
Solution Approach 1:
The system provides feedback to the user by returning the count of fulfilled items along with the requested data. This feedback mechanism informs users how much of their request was satisfied, enabling them to adjust future requests or understand system limitations without completely blocking data flow.
Solution Approach 2:
The system acts as an intermediary between resource constraints and user requests by processing requests through a filtering mechanism. It mediates between the user's desire for complete data and the system's resource limitations, delivering what is possible while preserving resources for future requests.
3Ease of operation
If the system processes data items without prioritization, then all items are treated equally, but processing time increases when resources are constrained
Solution Approach 1:
The system applies local quality by treating different data items differently based on their priority or importance. High-priority items are processed first and included in the first subset, while lower-priority items may be excluded or placed in subsequent subsets. This differentiated approach optimizes processing time by focusing resources on critical data.
Data Source
AI summary
To dynamically process requests for data items based on resource constraints, a computer system receives data including identifiers identifying respective data items. The data includes authorization request to obtain the multiple items and source data identifying a source. The system identifies a resource constraint associated with each of the data items and determines an aggregate resource constraint. If the aggregate exceeds a threshold, the system determines a subset of the multiple items. If an aggregate associated with data items in the subset satisfies the threshold, the system generates a first subset of the identifiers identifying respective data items in the determined subset, generates a second subset of the identifiers identifying respective data items excluded from the determined subset, transmits the authorization request to obtain the data items in the first subset, and transmits the permission, the first subset and the second subset to the source identified by the source data.