Reconfiguring Resolutions in Profiling Time and Energy on Android Applications

• Main Authors: Lai, Yu-Sheng, 賴育聖
• Other Authors: Lin, Ying-Dar
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/47793648075340066242

碩士 === 國立交通大學 === 資訊科學與工程研究所 === 99 === The computing of applications in embedded devices suffers tight constraints on computation and energy resources. Thus, applications spending long execution time and large energy consumption of embedded applications are not acceptable by users. The existing execution time and energy profiling tools can help developers to identify the bottlenecks of applications. However, the profiling tools need large memory space to store detailed profiling results at run time, causing that they are infeasible on embedded devices. In this thesis, a reconfigurable multi-resolution profiling (RMP) approach is proposed to handle the issue on off-the-shelf product devices. It instruments all profiling points into source code of targeted applications and configures the profiling points to change the profiling scope for filtering out useless profiling results to reduce the amount of profiling results. In the experiments, the required memory of profiling results using RMP for a browser application is smaller than debug class of Android 25 times, and the estimation error rate of execution time is proven lower than debug class 24 times because the debug class uses the entry time of java methods to calculate imprecise time results. Besides, the CPU and memory overhead of RMP are only 5% and 6.53% for the browsing scenario, respectively. From this evaluation, we found that the bottleneck of a browser is the web page drawing because the 2D graphical library does not use any hardware acceleration.