Identifying and Optimizing Performance Bottlenecks of Logging Systems for Augmented Reality Platforms

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Abstract

The logging system carries the task of collecting and analyzing key operation status and user interaction data in augmented reality (AR) platform. In this paper, we start from performance profiling to locate the performance bottlenecks of AR device logging service in high-frequency I/O scenarios, and propose a set of asynchronous write buffer mechanism, fast path optimization scheme, and flash-friendly compression strategy. In multiple rounds of real-world tests, the system can maintain a 15.4% CPU occupancy reduction and 41.7% write latency reduction under log write pressure. The study shows that the performance optimization of the logging system, as the underlying guarantee of system maintainability, is of key significance to platform stability.

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