Edge Device Performance Data Collection via Virtualization
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Solution Overview
Problem
The limited availability of devices at different locations constrains the ability to acquire comprehensive performance data for applications, hindering the identification and improvement of issues related to video or audio output, computational resource usage, and network conditions.
Innovation Solution
A system and method for configuring edge devices to determine test data during application execution, processing it locally to generate performance data that excludes private information, and sending it to servers for analysis, allowing for targeted acquisition of information from specific devices based on specified conditions without compromising user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple physical devices are deployed at different locations to collect performance data, then measurement precision and data comprehensiveness are improved, but device complexity and resource requirements increase
Solution Approach 1:
The patent uses virtual machine copies to simulate different device types and configurations. Instead of deploying multiple physical devices, the system creates virtual replicas of various device profiles (mobile phones, tablets, computers with different operating systems and hardware configurations) that can execute test applications and collect performance data remotely from a single centralized location.
Solution Approach 2:
The patent implements a universal testing platform that can emulate multiple device types and configurations within a single system. The virtual machine infrastructure allows one physical server to perform the functions of numerous different devices, enabling comprehensive performance measurement across diverse platforms without requiring separate physical devices for each test scenario.
2Productivity
If more devices are deployed to gather comprehensive performance metrics, then productivity of data collection is improved, but loss of substance (resources) increases
Solution Approach 1:
The system creates virtual copies of devices through virtual machines, allowing comprehensive performance data collection across multiple device profiles without the resource costs of physical hardware. These virtual instances can be instantiated, configured, and terminated on-demand, eliminating the need for continuous physical device deployment and reducing material resource consumption.
Solution Approach 2:
The patent replaces the mechanical/physical system of deploying actual hardware devices with a software-based virtualization system. Instead of physically transporting, installing, and maintaining multiple devices at different locations, the system uses software-defined virtual machines that can be remotely provisioned and managed, substituting physical resource consumption with computational resource utilization.
3Measurement precision
If test data is collected from user devices, then measurement precision is improved, but object-generated harmful factors (privacy concerns) increase
Solution Approach 1:
The patent introduces virtual machines as an intermediary layer between the test application and the user's physical device. The virtual machine executes the test application and collects performance data, acting as a mediator that prevents direct access to sensitive user information on the host device. This intermediary architecture allows real-world performance measurement while maintaining user privacy by isolating the testing environment from personal data.
Solution Approach 2:
The system segments the device environment into virtual machine instances that are isolated from the user's personal data and system resources. Each virtual machine is configured with specific device profiles and permissions, creating separate execution contexts that can collect performance metrics without accessing or exposing sensitive user information, applications, or files on the host device.
Data Source
AI summary
Devices at different geolocations are configured to determine and share information regarding execution of an application under various conditions. Data determined by a user device includes private information, such as screen capture data, location data, or information about the user. The user device processes the data locally, such as by determining performance metrics or other characteristics of execution of the application, and sends this information to a server. The data sent to the server excludes the private information. The server determines additional data associated with execution of the application by devices other than the user device, which may include screen capture data or location data associated with those other devices. The additional data is used in conjunction with the data received from the user device to generate interfaces indicative of performance metrics of the application.