With the rapid development of cloud computing and virtualization technology, more and more applications are being deployed and run in cloud environments, and compatibility issues between different browsers are becoming increasingly prominent. A browser compatibility performance detection method based on virtual cloud technology is proposed to address this issue. Using virtual cloud technology for environmental simulation, building a prediction model based on machine learning technology, predicting compatibility issues under different browser versions through this model, obtaining browser compatibility test data, and discovering patterns, trends, and patterns. Finally, build a browser compatibility performance test based on the Linux operating system to obtain the test results. The experimental results show that the detection results of this method have a high recall rate and a low false alarm rate. By increasing the number of test cases, it covers more situations and scenarios, improving the comprehensiveness of browser compatibility performance detection results.
In order to meet the requirements of interactivity, real-time and high efficiency of Internet of Things remote application system, the remote monitoring and analysis of sensor data of power Internet of Things is proposed. Through the combination of Lab VIEW Data Socket and JSP, a B/S-based Internet of Things-aware data publishing and remote monitoring system is constructed. The actual test results of the system show that the sensor data of the Internet of Things can be released and shared remotely in real time in the application process of the experimental site, and the related sensor data of the experimental site can be remotely monitored, managed and alarmed by the browser, which meets the requirements of interactivity, real-time and high efficiency of the remote application system of the Internet of Things.
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