{"id":69322,"updated":"2025-01-22T00:00:25.209544+00:00","links":{},"created":"2025-01-18T23:28:47.992151+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00069322","sets":["5471:5999"]},"path":["5999"],"owner":"11","recid":"69322","title":["A Ubiquitous Power Management System to Balance Energy Savings and Response Time Based on Devicelevel Usage Prediction"],"pubdate":{"attribute_name":"公開日","attribute_value":"2010-04-07"},"_buckets":{"deposit":"39e97273-1576-496e-ab0a-7d658cfa4fb6"},"_deposit":{"id":"69322","pid":{"type":"depid","value":"69322","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"A Ubiquitous Power Management System to Balance Energy Savings and Response Time Based on Devicelevel Usage Prediction","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"A Ubiquitous Power Management System to Balance Energy Savings and Response Time Based on Devicelevel Usage Prediction"},{"subitem_title":"A Ubiquitous Power Management System to Balance Energy Savings and Response Time Based on Devicelevel Usage Prediction","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Regular Paper","subitem_subject_scheme":"Other"}]},"item_type_id":"5","publish_date":"2010-04-07","item_5_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Research Center for Advanced Science and Technology, The University of Tokyo"},{"subitem_text_value":"Research Center for Advanced Science and Technology, The University of Tokyo"},{"subitem_text_value":"Research Center for Advanced Science and Technology, The University of Tokyo"},{"subitem_text_value":"Research Center for Advanced Science and Technology, The University of Tokyo"}]},"item_5_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Research Center for Advanced Science and Technology, The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Research Center for Advanced Science and Technology, The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Research Center for Advanced Science and Technology, The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Research Center for Advanced Science and Technology, The University of Tokyo","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/69322/files/IPSJ-JIP1800013.pdf"},"date":[{"dateType":"Available","dateValue":"2012-04-07"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JIP1800013.pdf","filesize":[{"value":"967.2 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"a90ff86c-85de-4f53-90c4-7329d34dd211","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2010 by the Information Processing Society of Japan"}]},"item_5_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hua, Si"},{"creatorName":"Shunsuke, Saruwatari"},{"creatorName":"Masateru, Minami"},{"creatorName":"Hiroyuki, Morikawa"}],"nameIdentifiers":[{}]}]},"item_5_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hua, Si","creatorNameLang":"en"},{"creatorName":"Shunsuke, Saruwatari","creatorNameLang":"en"},{"creatorName":"Masateru, Minami","creatorNameLang":"en"},{"creatorName":"Hiroyuki, Morikawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_5_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA00700121","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_5_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-6652","subitem_source_identifier_type":"ISSN"}]},"item_5_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"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.","subitem_description_type":"Other"}]},"item_5_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"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.","subitem_description_type":"Other"}]},"item_5_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"163","bibliographic_titles":[{"bibliographic_title":"Journal of information processing"}],"bibliographicPageStart":"147","bibliographicIssueDates":{"bibliographicIssueDate":"2010-04-07","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"18"}]},"relation_version_is_last":true,"weko_creator_id":"11"}}