智慧型手機的電力逐漸被重視，然而目前的耗電工具多是針對整支手機(系統層耗電)，較少工具能得知應用程式(程序層耗電)運行時的耗電資訊。因此如何建構更準確及有效能的程序層耗電模型為相當重要之議題。之前的研究Eprof利用耗電量測儀器量出耗電並與系統呼叫(System call)相互對應，以建構有限狀態機(Finite State Machine, FSM)，但在建構此FSM時採人工觀察的方式，故無一套有效率的方式來產生FSM，因此本研究自動建構FSM以提升建構FSM的效率及提升FSM的準確率。本論文提出一個結合系統呼叫及耗電以自動建構有限狀態機(Automatically Constructing Finite State Machine, ACFSM)之量測程序層耗電模型方法。ACFSM擷取智慧型手機元件的系統呼叫並搭配耗電量測儀器量出耗電，消除雜訊、過濾無用的系統呼叫並解決餘電以自動結合系統呼叫及耗電來建構FSM，餘電為當某硬體元件停止使用時，仍會有一段時間持續耗電。實驗結果分為效率及準確率兩方面，效率部分，ACFSM建構FSM時間只需413秒，人工建構FSM則需1394秒，因此ACFSM的效率增加了70%，準確率部分，解決餘電效應的誤差率為5.3%，沒有解決餘電的誤差率為10.9%，顯示有解決餘電比沒解決餘電的誤差率低51%。

Power consumption of smartphones is attached more importance. Most testing tools focus on the overall power consumption of smartphones (system-level power consumption), but few testing tools focus on the power consumption of applications (process-level power consumption). Therefore, constructing a process-level power model to increase the accuracy and efficiency is an important issue. Previous work, Eprof, uses a measurement tool to fetch power consumption, associate with system calls, and manually construct Finite State Machine (FSM), so it is an ineffective way. Our main contribution is automatically constructing FSM to raise construction efficiency and accuracy of FSM. This thesis provides a method, called Automatically Constructing FSM (ACFSM), to measure process-level power consumption. ACFSM fetches system call and maps power consumption, eliminate power noises, filter useless system calls, and solve Tail Power (TP) problem to automatically constructing FSM, where TP is that a hardware component still consumes power during a time period after it stops. Experiment results are divided in two parts: efficiency and accuracy. For efficiency, ACFSM needs 413 seconds but manually constructing FSM needs 1393 seconds, i.e., 70% improvement. For accuracy, the error rate of solving TP is 5.3% but that without solving TP is 10.9%. That is, ACFSM can achieve 51% improvement on the error rate, compared with the approach without considering TP.

[1]T. L. Cignetti, K. Komarov, and C. S. Ellis, "Energy Estimation Tools for The Palm," in Proceedings of the 3rd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems, Boston, Massachusetts, USA, 2000, pp.96-103.
[2]S. Gurumurthi, A. Sivasubramaniam, M. J. Irwin, N. Vijaykrishnan, and M. Kandemir, "Using Complete Machine Simulation for Software Power Estimation: The Softwatt Approach," in High-Performance Computer Architecture, 2002. Proceedings. Eighth International Symposium on, 2002, pp. 141-150.
[3]C. Yoon, D. Kim, W. Jung, C. Kang, and H. Cha, "AppScope: Application Energy Metering Framework for Android Smartphones using Kernel Activity Monitoring," in the Proceedings of the 2012 USENIX conference on Annual Technical Conference, Boston, MA, 2012, pp. 36-36.
[4]A. Pathak, Y. C. Hu, M. Zhang, P. Bahl, and Y.-M. Wang, "Fine-grained Power Modeling for Smartphones Using System Call Tracing," in Proceedings of the sixth conference on Computer systems, 2011, pp. 153-168
[5]A. Pathak, Y. C. Hu, and M. Zhang, "Where is the energy spent inside my app? Fine Grained Energy Accounting on Smartphones with Eprof," in Proceedings of the 7th ACM european conference on Computer Systems, 2012, pp. 29-42.
[6]J. Flinn and M. Satyanarayanan, "PowerScope: A Tool for Profiling the Energy Usage of Mobile Applications," in Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications, 1999, pp. 2-10.
[7]Baek, Woongki, Young-Jin Kim, and Jihong Kim, "ePRO: A Tool for Energy and Performance Profiler for Embedded Applications." in Proceedings. of International SoC Design Conference, 2004, p. 372-375.
[8]J. Lee, J. Hyunwoo, and K. Hyungshin, "Smart Phone Power Model Generation using use Pattern Analysis," in Proceedings of Consumer Electronics, 2012 IEEE International Conference on, 2012, pp. 412-413.
[9]R. Mittal, A. Kansal, and R. Chandra, "Empowering Developers to Estimate App Energy Consumption," in Proceedings of the 18th annual international conference on Mobile computing and networking, 2012, pp. 317-328.
[10]L. Zhang, B. Tiwana, Z. Qian, Z. Wang, R. P. Dick, Z. M. Mao, and L. Yang, "Accurate Online Power Estimation and Automatic Battery Behavior Based Power Model Generation for Smartphones," in Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis, 2010, pp. 105-114.
[11]A. Kansal and F. Zhao, "Fine-grained Energy Profiling for Power-aware Application Design," ACM SIGMETRICS Performance Evaluation Review, vol. 36, 2008, pp. 26-31.
[12]K. S. Banerjee and E. Agu, "Powerspy: Fine-grained Software Energy Profiling for Mobile Devices," in Wireless Networks, Communications and Mobile Computing, 2005 International Conference on, 2005, pp. 1136-1141.
[13]T. Do, S. Rawshdeh, and W. Shi, "pTop: A Process-level Power Profiling Tool," in Proceedings of the 2nd Workshop on Power Aware Computing and Systems, 2009.
[14]Bonetto, A., Ferroni, M., Matteo, D., Nacci, A. A., Mazzucchelli, M., Sciuto, D., and Santambrogio, M. D., "Mpower: Towards an Ddaptive Power Management System for Mobile Devices," in Computational Science and Engineering (CSE), 2012 IEEE 15th International Conference on, 2012, pp. 318-325.
[15]G. Metri, A. Agrawal, R. Peri, M. Brockmeyer, and W. Shi, "A Simplistic Way for Power Profiling of Mobile Devices," in Energy Aware Computing, 2012 International Conference on, 2012, pp. 1-6.
[16]M. Dong and L. Zhong, "Self-constructive High-rate System Energy Modeling for Battery-powered Mobile Systems," in Proceedings of the 9th international conference on Mobile systems, applications, and services, 2011, pp. 335-348.
[17]"Monsoon-Power Monitor," http://www.msoon.com/LabEquipment/PowerMonitor/.
[18]"Strace- Linux man page," http://linux.die.net/man/1/strace.