Inter-Domain Transaction Correlation via Execution Identifiers
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Solution Overview
Problem
Traditional transaction tracking technologies face challenges in building topology and correlating inter-domain transaction interactions, especially when static correlators cannot be passed between domains or common unique data is not available.
Innovation Solution
Collecting request-type and response-type event records with execution identifiers and unique tokens at each domain, allowing for matching and recording inter-domain transactions without using static or common correlators, and storing this data for future correlation processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If static correlators are passed between domains for transaction tracking, then transaction correlation accuracy is improved, but system complexity and security constraints are worsened
Solution Approach 1:
The patent uses execution identifiers (system ID, process ID, thread ID) as intermediary keys that naturally exist in the system to correlate transactions between domains, eliminating the need for separate static correlator mechanisms. This reduces system complexity while maintaining correlation accuracy.
Solution Approach 2:
The patent copies existing execution identifier data that is already present in the system into the correlation data store, rather than creating and passing separate correlator objects between domains. This approach simplifies the system architecture while enabling accurate transaction matching.
2Measurement precision
If dynamic correlators are generated using common unique data, then transaction correlation is improved, but adaptability to systems without common data is worsened
Solution Approach 1:
The patent uses execution identifiers (system ID, process ID, thread ID) that are universally available in any operating system environment, making the correlation mechanism adaptable to any system regardless of whether common unique data exists between domains. These identifiers serve multiple purposes: process identification and transaction correlation.
Solution Approach 2:
The patent changes the correlation approach from using domain-specific common data to using execution identifiers with associated timestamps. This parameter change enables the system to work in any environment where processes execute, removing the constraint of requiring pre-existing common unique data between domains.
3Measurement precision
If traditional correlator methods are used, then transaction matching capability is improved, but ease of operation and implementation are worsened
Solution Approach 1:
The system uses self-generated execution identifiers and timestamps that automatically serve as correlation keys. Each domain independently generates and stores these identifiers with event records, and the correlation is achieved by matching these self-service identifiers without requiring external correlator management infrastructure.
4Loss of information
If event records are collected and stored for correlation, then transaction analysis capability is improved, but data storage requirements are worsened
Solution Approach 1:
The patent extracts only the essential correlation elements (execution identifiers and timestamps) from the event data and stores them in the correlation data store. This extraction approach enables transaction analysis while minimizing storage requirements by keeping only the necessary matching keys rather than duplicating entire event records.
Data Source
AI summary
An approach is provided to correlate transaction data occurring at two different domains running on a common operating system image without using static, or common, correlators. Request-type event records are collected at a first domain within the operating system image, with each of the request-type event records including execution identifiers and a unique token that indicates the order in which the corresponding request-type event occurred on the first domain. Similarly, response-type event records are collected at a second domain within the operating system image. The request-type event records are matched with the response-type event records based on the execution identifiers and an overall order that is indicated by unique tokens included in the records. The matching of request-type event records with response-type event records indicate a number of inter-domain transactions which are recorded in a correlation data store.


