A Ubiquitous Power Management System to Balance Energy Savings and Response Time Based on Devicelevel Usage Prediction

• Item type: JInfP(1)
• 公開日: 2010-04-07
• タイトル: A Ubiquitous Power Management System to Balance Energy Savings and Response Time Based on Devicelevel Usage Prediction
• タイトル / 言語: en
• タイトル: A Ubiquitous Power Management System to Balance Energy Savings and Response Time Based on Devicelevel Usage Prediction
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: Regular Paper
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Research Center for Advanced Science and Technology, The University of Tokyo
• 著者所属: Research Center for Advanced Science and Technology, The University of Tokyo
• 著者所属: Research Center for Advanced Science and Technology, The University of Tokyo
• 著者所属: Research Center for Advanced Science and Technology, The University of Tokyo
• 著者所属(英): en
• 著者所属(英): Research Center for Advanced Science and Technology, The University of Tokyo
• 著者所属(英): en
• 著者所属(英): Research Center for Advanced Science and Technology, The University of Tokyo
• 著者所属(英): en
• 著者所属(英): Research Center for Advanced Science and Technology, The University of Tokyo
• 著者所属(英): en
• 著者所属(英): Research Center for Advanced Science and Technology, The University of Tokyo
• 著者名: Hua, Si; Shunsuke, Saruwatari; Masateru, Minami; Hiroyuki, Morikawa
• 著者名(英): Hua, Si; Shunsuke, Saruwatari; Masateru, Minami; Hiroyuki, Morikawa
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Power conservation has become a serious concern during people's daily life. Ubiquitous computing technologies clearly provide a potential way to help us realize a more environment-friendly lifestyle. In this paper, we propose a ubiquitous power management system called Gynapse, which uses multi-modal sensors to predict the exact usage of each device, and then switches their power modes based on predicted usage to maximize the total energy saving under the constraint of user required response time. We build a three-level Hierarchical Hidden Markov Model (HHMM) to represent and learn the device level usage patterns from multi-modal sensors. Based on the learned HHMM, we develop our predictive mechanism in Dynamic Bayesian Network (DBN) scheme to precisely predict the usage of each device, with user required response time under consideration. Based on the predicted usage, we follow a four-step process to balance the total energy saving and response time of devices by switching their power modes accordingly. Preliminary results demonstrate that Gynapse has the capability to reduce power consumption while keeping the response time within user's requirement, and provides a complementary approach to previous power management systems.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Power conservation has become a serious concern during people's daily life. Ubiquitous computing technologies clearly provide a potential way to help us realize a more environment-friendly lifestyle. In this paper, we propose a ubiquitous power management system called Gynapse, which uses multi-modal sensors to predict the exact usage of each device, and then switches their power modes based on predicted usage to maximize the total energy saving under the constraint of user required response time. We build a three-level Hierarchical Hidden Markov Model (HHMM) to represent and learn the device level usage patterns from multi-modal sensors. Based on the learned HHMM, we develop our predictive mechanism in Dynamic Bayesian Network (DBN) scheme to precisely predict the usage of each device, with user required response time under consideration. Based on the predicted usage, we follow a four-step process to balance the total energy saving and response time of devices by switching their power modes accordingly. Preliminary results demonstrate that Gynapse has the capability to reduce power consumption while keeping the response time within user's requirement, and provides a complementary approach to previous power management systems.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA00700121
• 書誌情報: Journal of information processing; 巻 18, p. 147-163, 発行日 2010-04-07
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-6652
• 出版者 / 言語: ja
• 出版者: 情報処理学会