智慧型手機開始逐漸蓬勃發展，手機用戶數不斷提升及手機應用程式快速普及化，但在使用上仍然受到手機電池壽命的限制，並且多核心智慧型手機的時代開始來臨，對於多核心智慧型手機的耗電量測也是個重要的課題。多核心手機裝置為提升手機效能，利用多顆CPU的方式進而分擔整體的工作量，以達平行處理的效果，但在分擔工作量的情形下容易互相影響各自的使用率，因此先前的研究將各CPU視為獨立的參數，可能無法精確地得到裝置的耗電量。
因此本論文將提出一個多核心電力量測模型(Multi-core Power Estimation Model, MPEM)，MPEM以資源使用率模型(Utilization based, UB)為基礎，首先透過擷取手機耗電量及CPU使用率的資料，再以迴歸分析的方法建立一個有效的電力量測模型，並為精確考量CPU的耗電因素，將CPU使用率間的關聯性列入耗電考量並提出Dependent CPU Utilization (DCU)及Load-based CPU Utilization(LCU)兩個耗電量測公式。實驗結果與先前的研究做比較，得知DCU相較於先前的作法可以改善5%至10%的錯誤率，並且LCU結果相較於DCU改善約5%至10%的錯誤率。

Smartphones are wide spread and the number of smartphone users and applications are continuously increasing. One of the most nerve-wracking concerns to the users is full discharge of battery. Since there are more multi-core smartphones, it becomes important to measure the power consumption of multi-core smartphones. In order to improve the performance, the multi-core smartphones use multiple CPUs to share the workload with parallel processing. However, the CPU utilization will influence each other in these devices. Previous studies assume the CPU utilization in smartphones as an independent parameter, causing their power consumption is not accurately estimated.
In this thesis, we propose a Multi-core Power Estimation Model (MPEM) according to a Utilization Based approach (UB). MPEM first measures the power consumption and CPU utilization, and then uses the regression analysis to build an effective power consumption model. To more precisely consider the power consumption factors on CPU, MPEM uses the associate CPU utilization. MPEM has two power formulas, Dependent CPU Utilization (DCU) and Load-based CPU Utilization (LCU). Experiment results show that DCU has decrease 5%~10% error rate, compared with the previous work. Also LCU has only 10% error rate, that is, it has a lower error rate about 5%~10% than DCU.

[1] S. K. Datta, C. Bonnet, and N. Nikaein, "Android Power Management: Current and Future Trends," in Enabling Technologies for Smartphone and Internet of Things (ETSIoT), 2012 First IEEE Workshop on, 2012, pp. 48-53.
[2] A. Sagahyroon, "Power Consumption in Handheld Computers," in Circuits and Systems, 2006. APCCAS 2006. IEEE Asia Pacific Conference on, 2006, pp. 1721-1724.
[3] 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.
[4] S. Gurumurthi, A. Sivasubramaniam, M. J. Irwin, N. Vijaykrishnan, M. Kandemir, T. Li, and L. K. John, "Using Complete Machine Simulation for Software Power Estimation: The SoftWatt Approach," in Proceedings of the 8th International Symposium on High-Performance Computer Architecture, 2002, pp. 141.
[5] 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.
[6]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.
[7] 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.
[8] W. Jung, C. Kang, C. Yoon, D. Kim, and H. Cha, "DevScope: A Nonintrusive and Online Power Analysis Tool for Smartphone Hardware Components," in Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis, Tampere, Finland, 2012, pp. 353-362.
[9] N. Vallina-Rodriguez and J. Crowcroft, "Energy Management Techniques in Modern Mobile Handsets," Communications Surveys & Tutorials, IEEE, vol. 15, 2013, pp. 179-198.
[10] 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.
[11] 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.
[12] J. Lee, J. Hyunwoo, and K. Hyungshin, "Smart Phone Power Model Generation Using Use Pattern Analysis," in Consumer Electronics (ICCE), 2012 IEEE International Conference on, 2012, pp. 412-413.
[13] K. Minyong, K. Joonho, and C. Sung Woo, "Enhancing Online Power Estimation Accuracy for Smartphones," Consumer Electronics, IEEE Transactions on, vol. 58, 2012, pp. 333-339.
[14] K. Minyong, K. Joonho, and C. Sung Woo, "An Online Power Estimation Technique for Multi-core Smartphones with Advanced Display Components," in Consumer Electronics (ICCE), 2012 IEEE International Conference on, 2012, pp. 666-667.
[15] T. Kamiyama, H. Inamura, and K. Ohta, "A Model-based Energy Profiler Using Online Logging for Android Applications," in Mobile Computing and Ubiquitous Networking (ICMU), 2014 Seventh International Conference on, 2014, pp. 7-13.