Electronic Message Matching Using Two-Sided Sum Filtering
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Solution Overview
Problem
Existing computing systems face challenges in efficiently allocating processing resources to optimize the matching of electronic data messages, particularly in high-volume and high-speed environments such as automated computer exchanges, where increasing resources may not be feasible or desirable.
Innovation Solution
A method involving the use of two sorted lists, where one list is designated as 'aggressive' and the other as 'passive', with a sum of values calculated to determine matches while skipping messages exceeding a minimum requirement, allowing for efficient matching without complex combinatorial optimizations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional matching algorithms are used to match electronic data messages, then all possible matches can be found, but the processing time and computational resources increase significantly
Solution Approach 1:
The patent segments the matching process into two distinct phases: a filtering phase that quickly eliminates non-matching messages using the sum rule, and a detailed matching phase that processes only the filtered subset. This segmentation reduces the overall computational burden while maintaining complete match accuracy.
Solution Approach 2:
The patent performs preliminary filtering using the sum rule calculation before conducting detailed message matching. By calculating the sum of data fields and comparing against minimum requirements in advance, the system eliminates obviously non-matching messages before they consume resources in the detailed matching phase.
2Productivity
If processing resources are increased to handle high-volume message matching, then matching speed improves, but system cost and complexity increase
Solution Approach 1:
The system uses the inherent data fields within the electronic messages themselves (such as size, quantity, or value fields) to perform the filtering operation. By leveraging existing message attributes for the sum rule calculation, the system avoids introducing additional complex infrastructure while achieving efficient resource allocation.
3Manufacturing precision
If comprehensive matching criteria are applied to ensure minimum requirements are met, then match quality improves, but the number of comparisons and processing steps increases
Solution Approach 1:
The patent extracts and applies the sum rule as a separate, standalone filtering criterion before the main matching process. By taking out this preliminary check and applying it independently to eliminate non-matching messages early, the system ensures minimum requirements are met while reducing the complexity of the subsequent detailed matching process.
Data Source
AI summary
A computer system includes a memory that stores two lists of electronic data transaction requests. Stored and received data transaction requests are associated with a size value and a counter-size requirement value. When data transaction requests are received they are added to one of the two lists and list to which the data transaction request is added is set to a working side. A working order is selected from the working side and a first sum of size values of data transaction requests is calculated from the working side. A second sum of size values is calculated from the non-working side from data transaction requests that have a counter-size requirement value that is less than the first sum. If the counter-size requirement value is less than or equal to the second sum, the electronic data requests from the respective lists are matched.