Resource Distribution Control Parameters
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Resource management systems face inefficiencies due to users setting control parameters that are too restrictive or too permissive, leading to excessive resource distribution denials or unauthorized transactions, which consume computing and network resources.
Innovation Solution
A system that determines suggested control parameters based on historical data of resource distributions, provides these to users, and allows users to input user-defined parameters, thereby reducing the likelihood of overly restrictive or permissive settings by optimizing resource distribution authorization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually set control parameters for resource distribution, then users can control resource allocation, but the parameters may be too restrictive or too permissive leading to excessive denials or unauthorized transactions
Solution Approach 1:
The system performs preliminary analysis of historical resource distribution data before users set control parameters. By pre-processing the data and identifying optimal parameter ranges based on past patterns, the system prepares suggested parameters in advance, guiding users to make more accurate settings and reducing the likelihood of overly restrictive or permissive configurations.
Solution Approach 2:
The system analyzes historical resource distribution data to generate feedback about optimal control parameter settings. This feedback loop provides users with data-driven suggestions based on actual usage patterns, enabling them to adjust parameters more accurately and avoid extreme settings that lead to excessive denials or unauthorized transactions.
2Reliability
If control parameters are set too restrictively, then unauthorized transactions are reduced, but legitimate resource distributions are excessively denied
Solution Approach 1:
The system pre-analyzes historical data to establish baseline patterns of legitimate resource distributions before applying control parameters. By understanding normal distribution patterns in advance, the system can configure parameters that maintain security while preserving legitimate transactions, preventing excessive denials of valid resource requests.
Solution Approach 2:
The system applies control parameters selectively based on historical patterns rather than uniformly across all transactions. By identifying specific patterns of legitimate distributions from historical data, the system applies restrictions only where necessary for security, allowing partial exemptions that maintain productivity while ensuring security for high-risk transactions.
3Productivity
If control parameters are set too permissively, then legitimate resource distributions are authorized, but unauthorized transactions are permitted
Solution Approach 1:
The system continuously monitors resource distribution outcomes and feeds this information back into the parameter optimization process. By analyzing both authorized and denied transactions against historical patterns, the system refines control parameters to maintain high authorization rates for legitimate transactions while progressively tightening security for potentially unauthorized distributions.
Solution Approach 2:
The system pre-configures control parameters based on historical analysis before they are applied to actual transactions. This preliminary setup ensures that parameters are optimized for both productivity and security from the start, preventing the system from being overly permissive while maintaining high authorization rates for legitimate distributions.
4Measurement precision
If the system processes and analyzes historical data to determine optimal control parameters, then parameter accuracy is improved, but computing and network resources are consumed
Solution Approach 1:
The system performs partial analysis of historical data by focusing on specific relevant patterns and metrics rather than processing every detail of the complete dataset. By identifying and analyzing only the most significant patterns in historical resource distributions, the system achieves sufficient parameter accuracy while reducing the computational burden and resource consumption associated with comprehensive data processing.
Data Source
AI summary
Systems, computer program products, and methods are described herein for establishment and dynamic adjustment of control parameters associated with resource distribution. The present invention may be configured to determine, based on historical data of resource distributions, suggested control parameters for resource distributions associated with a source associated with a user and provide the suggested control parameters to the user. The present invention may be configured to receive, after providing the suggested control parameters to the user, user input identifying user-defined control parameters. The present invention may be configured to receive a request to authorize a resource distribution, determine, based on the user-defined control parameters, whether the resource distribution is permitted, and authorize, based on determining that the resource distribution is permitted, the resource distribution.