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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/77838完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 郭大維 | |
| dc.contributor.author | Yi-Ying He | en |
| dc.contributor.author | 何宜穎 | zh_TW |
| dc.date.accessioned | 2021-07-11T14:35:46Z | - |
| dc.date.available | 2022-09-04 | |
| dc.date.copyright | 2017-09-04 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-08-20 | |
| dc.identifier.citation | [1] Simon Khalaf and Lali Kesiraju. U.s. consumers time-spent on mobile crosses 5 hours a day. https://goo.gl/jTURe7, 2017. [Online; accessed 2017-12-28].
[2] Ayaz Nanji. Mobile app usage and download trends for 2016. https://goo.gl/4jusQ9, 2016. [Online; accessed 2017-12-28]. [3] Statista. Number of mobile monthly active facebook users worldwide. https://goo.gl/VpyuSH, 2017. [Online; accessed 2017-12-28]. [4] Jay McGregor. Facebook is rapidly draining your battery: Here’s one easy fix. https://goo.gl/snF45w, 2014. [Online; accessed 2017-12-28]. [5] Dongwon Kim, Nohyun Jung, and Hojung Cha. Content-centric display energy management for mobile devices. In Proceedings of the 51st Annual Design Automation Conference, pages 1–6. ACM, 2014. [6] Haofu Han, Jiadi Yu, Hongzi Zhu, Yingying Chen, Jie Yang, Guangtao Xue, Yanmin Zhu, and Minglu Li. E 3: energy-efficient engine for frame rate adaptation on smartphones. In Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems, page 15. ACM, 2013. [7] Google. Android graphic. https://source.android.com/devices/graphics/, 2017. [Online; accessed 2017-12-28]. [8] Karthik Rao, Jun Wang, Sudhakar Yalamanchili, Yorai Wardi, and Ye Handong. Application-specific performance-aware energy optimization on android mobile devices. In High Performance Computer Architecture (HPCA), 2017 IEEE International Symposium on, pages 169–180. IEEE, 2017. [9] Li Li, Jun Wang, Xiaorui Wang, Handong Ye, and Ziang Hu. Sceneman: Bridging mobile apps with system energy manager via scenario notification. In Low Power Electronics and Design (ISLPED, 2017 IEEE/ACM International Symposium on, pages 1–6. IEEE, 2017. [10] Brad K Donohoo, Chris Ohlsen, and Sudeep Pasricha. Aura: An application and user interaction aware middleware framework for energy optimization in mobile devices. In Computer Design (ICCD), 2011 IEEE 29th International Conference on, pages 168–174. IEEE, 2011. [11] Kaige Yan, Xingyao Zhang, Jingweijia Tan, and Xin Fu. Redefining qos and customizing the power management policy to satisfy individual mobile users. In Microarchitecture (MICRO), 2016 49th Annual IEEE/ACM International Symposium on, pages 1–12. IEEE, 2016. [12] Xianfeng Li, Guikang Chen, and Wen Wen. Energy-efficient execution for repetitive app usages on big. little architectures. In Design Automation Conference (DAC), 2017 54th ACM/EDAC/IEEE, pages 1–6. IEEE, 2017. [13] Huseyin Bicen and Nadire Cavus. Social network sites usage habits of undergraduate students: Case study of facebook. Procedia-Social and Behavioral Sciences, 28:943–947, 2011. [14] Google. Android cpu governors. https://goo.gl/c1vgqt, 2017. [Online; accessed 2017-12-28]. [15] Yuhao Zhu, Matthew Halpern, and Vijay Janapa Reddi. Event-based scheduling for energy-efficient qos (eqos) in mobile web applications. In High Performance Computer Architecture (HPCA), 2015 IEEE 21st International Symposium on, pages 137–149. IEEE, 2015. [16] Benjamin Gaudette, Carole-Jean Wu, and Sarma Vrudhula. Improving smartphone user experience by balancing performance and energy with probabilistic qos guarantee. In High Performance Computer Architecture (HPCA), 2016 IEEE International Symposium on, pages 52–63. IEEE, 2016. [17] Daniel Lo, Taejoon Song, and G Edward Suh. Prediction-guided performanceenergy trade-off for interactive applications. In Microarchitecture (MICRO), 2015 48th Annual IEEE/ACM International Symposium on, pages 508–520. IEEE, 2015. [18] Nohyun Jung, Gwangmin Lee, Seokjun Lee, and Hojung Cha. Tbooster: Adaptive touch boosting for mobile texting. In Proceedings of the 17th International Workshop on Mobile Computing Systems and Applications, pages 63–68. ACM, 2016. [19] Wook Song, Nosub Sung, Byung-Gon Chun, and Jihong Kim. Reducing energy consumption of smartphones using user-perceived response time analysis. In Proceedings of the 15th Workshop on Mobile Computing Systems and Applications, page 20. ACM, 2014. [20] Monsoon Solutions Inc. Monsoon power monitor. https://www.msoon.com/, 2017. [Online; accessed 2017-12-28]. [21] Cygery. Repetitouch for android. https://cygery.com/wordpress/apps/repetitouch/, 2017. [Online; accessed 2017-12-28]. [22] James RB Bantock, Vasileios Tenentes, Bashir M Al-Hashimi, and Geoff V Merrett. Online tuning of dynamic power management for efficient execution of interactive workloads. In Low Power Electronics and Design (ISLPED, 2017 IEEE/ACM International Symposium on, pages 1–6. IEEE, 2017. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/77838 | - |
| dc.description.abstract | 社群應⽤程式在⼿機應⽤程式使⽤上佔有重要地位。雖然社群應⽤並⾮如⼿機遊戲耗電，在使⽤上依舊有浪費電⼒的問題。本篇論⽂提出使⽤者使⽤情形為考量的CPU 管理⽅法。我們考慮使⽤者在進⾏與社群應⽤互動的觸控模式，辨認出使⽤者的使⽤狀態，藉以該狀態下的資源使⽤特性來調整CPU以達到省電效果。實驗結果顯⽰，我們的⽅法在最⾼可以達到約25% 的省電⽽且幾乎不會影響使⽤者經驗，⽽我們的⽅法造成的電池負擔僅有閒置狀態的4.7%。 | zh_TW |
| dc.description.abstract | Mobile social applications are highly popular among smartphone users. While such apps are not as power hungry as mobile games, their extensive use can still drain device batteries. This paper proposes an usage-aware CPU governing method which considers user input patterns when interacting with social applications to adjust CPU frequency in accordance with usage state and active features to enhance power efficiency. Experimental results show our proposed method produces energy savings of up to 25% with minimal impact on the user experience and an idling overhead of about 4.7%. | en |
| dc.description.provenance | Made available in DSpace on 2021-07-11T14:35:46Z (GMT). No. of bitstreams: 1 ntu-106-R04922046-1.pdf: 1083248 bytes, checksum: ddbf1504fc3685d4101cfa4b272de127 (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
中文摘要 ii Abstract iii Contents iv List of Figures vi List of Tables vii 1 Introduction 1 2 Background and Observations 3 2.1 CPU Governing Methods on Android Devices 3 2.2 QoS Quantization 4 2.3 Observations 4 3 Usage-Aware Governing 8 3.1 Framework Overview 8 3.2 Usage Classifier 9 3.3 QoS Monitor 10 3.4 Policy Manager 11 4 Evaluation 14 4.1 Experiment Setup 14 4.2 Evaluation with Usage-Aware Governance 15 4.3 Framework Overhead 17 5 Related Works 19 6 Conclusions 20 Bibliography 21 | |
| dc.language.iso | en | |
| dc.title | 手機社群應用之基於使用模式考量的CPU管理 | zh_TW |
| dc.title | Usage-Aware CPU Governing for Mobile Social Applications | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 105-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 修丕承 | |
| dc.contributor.oralexamcommittee | 徐慰中,劉邦鋒,楊佳玲 | |
| dc.subject.keyword | 社群應用,節能,CPU管理,Android, | zh_TW |
| dc.subject.keyword | Social application,Energy saving,CPU governing,Android, | en |
| dc.relation.page | 23 | |
| dc.identifier.doi | 10.6342/NTU201703609 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2017-08-20 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-106-R04922046-1.pdf 目前未授權公開取用 | 1.06 MB | Adobe PDF |
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