Geostreaming System Pattern-Based Test Data Generation
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Solution Overview
Problem
Traditional database systems are inadequate for handling continuous data streams with geospatial information, as they are designed for finite data sets and lack the processing flexibility required for modern applications such as stock quote monitoring and automobile traffic management, which generate real-time, unbounded data.
Innovation Solution
A Geostreaming system with a Complex Event Processor (CEP) that uses pattern-based test data generation and level of detail control to efficiently process and visualize geospatial data streams, including geofence, in-route/out-of-route, and moving object tracking patterns, by abstracting complex algorithms and reducing polygon complexity through simplification algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional database systems are used to store and query data, then data can be managed in structured tables with SQL queries, but the system cannot handle continuous unbounded data streams effectively
Solution Approach 1:
The system segments data handling into two distinct components: a traditional database for finite structured data and a separate stream processing engine for continuous unbounded data streams. This segmentation allows each component to specialize in its appropriate data type while maintaining overall system functionality.
Solution Approach 2:
The patent introduces an intermediary layer that bridges traditional database systems and modern stream processing requirements. This intermediary enables SQL-like queries to operate on stream data while maintaining compatibility with existing database infrastructure.
2Productivity
If SQL queries are executed on finite data sets, then queries produce static results, but the system lacks the capability to perform long-running queries over continuous data streams
Solution Approach 1:
The system pre-compiles and optimizes query plans for stream processing, preparing execution strategies in advance before actual data streams arrive. This preliminary action enables faster query execution when continuous data flows through the system.
Solution Approach 2:
The stream processing engine maintains continuous query execution over unbounded data streams, unlike traditional SQL that executes once on finite sets. Queries run continuously, processing data as it arrives and providing ongoing insights without interruption.
3Adaptability or versatility
If product suites are offered for event stream processing, then basic stream handling capability is provided, but processing flexibility for complex geospatial patterns is insufficient
Solution Approach 1:
The patent extracts complex geospatial pattern matching logic from general stream processing frameworks and implements specialized algorithms for specific patterns like geofencing, in-route detection, and moving object tracking. This extraction provides targeted flexibility for geospatial applications.
Solution Approach 2:
The system applies different processing strategies and optimization techniques tailored to specific geospatial patterns. Each pattern type (geofence, in-route, tracking) receives customized handling with appropriate complexity levels, rather than using a one-size-fits-all approach.
4Reliability
If complex algorithms are used for pattern recognition in data streams, then accurate pattern detection is achieved, but computational load increases and performance decreases
Solution Approach 1:
The system applies partial pattern matching and filtering, processing only the portion of data necessary to detect specific patterns. Not all data requires full complex algorithmic analysis - selective application of computational resources maintains accuracy while improving throughput.
Solution Approach 2:
The system dynamically adjusts processing parameters based on data characteristics and pattern requirements. By changing parameters such as matching thresholds, window sizes, and algorithm selection, the system optimizes the balance between detection accuracy and processing speed for different scenarios.
Data Source
AI summary
Systems and methods described herein are directed towards a test data generator. In some examples, a reference polygon may be received from an application. Additionally a control parameter may be received from the application. Two points on a map may be selected and a path between the two points may be generated. Additional points may be created along the path and test may be generated by processing the additional points. The test data may be provided to the application.