@INPROCEEDINGS{xu:rtas2019, author={X. {Zhang} and X. {Xiao} and L. {He} and Y. {Ma} and Y. {Huang} and X. {Liu} and W. {Xu} and C. {Liu}}, booktitle={2019 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS)}, title={PIFA: An Intelligent Phase Identification and Frequency Adjustment Framework for Time-Sensitive Mobile Computing}, year={2019}, volume={}, number={}, pages={54-64}, keywords={energy conservation;knowledge based systems;mobile computing;power aware computing;energy efficient;desirable latency performance;PIFA;different execution phases;phase identification results;runtime frequency adjustment;real-world Android applications;multiple app categories;desired latency requirement;time-sensitive mobile computing;battery capacity;mobile devices;CPU power governors;dynamic frequency adjustment schemes;CPU energy consumption;important fact;real-world applications;multiple execution phases;different functionality;different amounts;unified app-level frequency setting;different phases;energy reduction;intelligent phase identification;frequency adjustment framework;energy-efficient application;DVFS;mobile computing;phase identification;time-sensitive}, doi={10.1109/RTAS.2019.00013}, ISSN={}, month={April},}