Intelligent Distributed Test Management for 5G User Devices
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Solution Overview
Problem
Current approaches for running user trials for technologies like 5G cellular network technology face challenges, including the need for specific test definitions and user interaction, which can deter participation and delay the collection of necessary test data.
Innovation Solution
The system intelligently manages distributed tests by obtaining device data from user devices, generating usage prediction models, determining predicted usage context, and identifying suitable tests for automatic execution based on device configuration and predicted usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If tests are specifically defined and require user interaction, then test execution can be controlled and directed, but user participation becomes more difficult and test data collection is delayed
Solution Approach 1:
The system enables user devices to automatically execute tests without requiring user interaction. The test execution is self-service in nature, where the distributed testing system autonomously manages test deployment, execution, and data collection across multiple user devices, eliminating the need for users to manually participate in test activities.
Solution Approach 2:
The system performs preliminary actions by pre-configuring and deploying tests to user devices before actual test execution is needed. Test definitions, configurations, and necessary software components are prepared in advance and distributed to target devices, enabling automatic execution when conditions are met without requiring real-time user involvement.
2Measurement precision
If manual user interaction is required for test execution, then test conditions can be precisely controlled, but test data collection time increases
Solution Approach 1:
The system accelerates the test data collection process by implementing automatic test execution across distributed user devices. This exponentially speeds up data collection compared to manual methods, while the system maintains precise control over test conditions through automated configuration management and execution protocols.
Solution Approach 2:
The testing system is segmented into independent distributed components across multiple user devices. Each device autonomously executes test segments according to predefined configurations, allowing parallel execution that reduces overall data collection time while maintaining precise control over individual test conditions through centralized management.
3Quantity of substance
If distributed testing is implemented without intelligent management, then more devices can participate in testing, but test execution efficiency and data quality decrease
Solution Approach 1:
The intelligent test management system provides universal functionality that adapts to diverse user devices and test types. It implements multi-functional capabilities including automatic test selection, configuration adaptation, execution monitoring, and data aggregation, enabling efficient management of large-scale distributed testing across heterogeneous device environments.
Solution Approach 2:
The system implements feedback mechanisms where test execution results, device status information, and performance data are continuously collected and analyzed. This feedback enables dynamic adjustment of test configurations, optimal device selection for specific tests, and quality control measures that maintain high execution efficiency and data quality across the distributed device network.
Data Source
AI summary
The disclosure herein describes intelligently managing distribution of tests to user devices. Test definition data of a target test is obtained by a processor of a testing platform. A set of user devices is identified for executing the target test from a plurality of available user devices. Identifying the set of user devices includes, for each user device, analyzing device configuration data and predicted usage context data using test requirements of the test definition data, identifying a likelihood that the user device will enter a required device state during a test interval of the target test, and determining an average likelihood data value for the set of user devices satisfies the test requirements. Test execution control signals are sent to each user device of the set of user devices and test results associated with execution of the target test are received from the set of user devices.