| Summary: | 碩士 === 國立交通大學 === 資訊學院碩士在職專班資訊組 === 98 === Android-based systems perform slowly in three perceptible scenarios: booting, browsing, and streaming. Time profiling on Android devices encounters three unique properties: 1) the execution flow of a scenario invokes multiple software layers, 2) each software layer is implemented in different programming languages, and 3) log space is limited. This thesis proposes a staged iterative instrumentation approach that starts profiling a scenario from a single module, restrainedly profiles more modules and layers to avoid enormous irrelevant profiling results, and finally consolidates the profiling results from different layers to find out the bottlenecks. Experiments on the off-the-shelf Android product showed that 72% of booting time is spent on the initialization of user-space environment; specifically, 44.4% of user-space initialization time is to start Android services and managers, and 39.2% is for preloading Java classes and resources. Experimental results also showed that the networking technology is the most significant factor influencing the browsing performance on Android. The time of drawing screen only takes less than 5% of total time for browsing a 2128 kB web page. In the streaming scenario, video preparation causes 5.7% time overhead for playing a 22-MB video file over Wi-Fi connection. Execution time of Video-downloading and data-decoding take 72% ratio of preparation time.
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