{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00210324","sets":["6164:6165:9654:10560"]},"path":["10560"],"owner":"44499","recid":"210324","title":["Predictive Many-core Allocation Method for Edge Off-Road Services"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-15"},"_buckets":{"deposit":"a0e6c925-5d41-4a8f-82d2-3d87014311b1"},"_deposit":{"id":"210324","pid":{"type":"depid","value":"210324","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Predictive Many-core Allocation Method for Edge Off-Road Services","author_link":["532179","532173","532174","532177","532175","532178","532176","532172"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Predictive Many-core Allocation Method for Edge Off-Road Services"},{"subitem_title":"Predictive Many-core Allocation Method for Edge Off-Road Services","subitem_title_language":"en"}]},"item_type_id":"18","publish_date":"2021-03-15","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Department of Information Science and Engineering, College of Engineering, Shibaura Institute of Technology"},{"subitem_text_value":"VA Linux Systems Japan K K"},{"subitem_text_value":"Tokai University"},{"subitem_text_value":"Department of Information Science and Engineering, College of Engineering, Shibaura Institute of Technology"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Information Science and Engineering, College of Engineering, Shibaura Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"VA Linux Systems Japan K K","subitem_text_language":"en"},{"subitem_text_value":"Tokai University","subitem_text_language":"en"},{"subitem_text_value":"Department of Information Science and Engineering, College of Engineering, Shibaura Institute of Technology","subitem_text_language":"en"}]},"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/210324/files/IPSJ-APRIS2020008.pdf","label":"IPSJ-APRIS2020008.pdf"},"date":[{"dateType":"Available","dateValue":"2021-03-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-APRIS2020008.pdf","filesize":[{"value":"1.7 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"42"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"ca889c48-887a-4604-8f3a-91d75028a5d7","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Masato, Fukui"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yoichi, Ishiwata"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Ohkawa"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Midori, Sugaya"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Masato, Fukui","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yoichi, Ishiwata","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Ohkawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Midori, Sugaya","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"In recent years, edge computing has been attracting attention for the purpose of offloading advanced processing by IoT and robot services. It needs to efficiently provide services to multiple robotics services while dynamically switching abundant computational resources such as many-core resources. In Many-core research, many studies have been conducted to increase the degree of parallelism of tasks to improve responsiveness and computational efficiency. However, there is still not enough discussion on how to effectively allocate resources in a way that is suitable for integrated services and to achieve both efficiency and responsiveness. In this study, we construct an efficient resource allocation prediction formula as a study of an efficient Many-core allocation method for edge offload. In addition, as a specific service, we decided to evaluate the offload of AI processing of communication robots. In the construction of the prediction formula, it was confirmed that sufficient processing performance and responsiveness can be obtained with the minimum core by automatically calculating the optimum number of cores from the actual application operation.","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In recent years, edge computing has been attracting attention for the purpose of offloading advanced processing by IoT and robot services. It needs to efficiently provide services to multiple robotics services while dynamically switching abundant computational resources such as many-core resources. In Many-core research, many studies have been conducted to increase the degree of parallelism of tasks to improve responsiveness and computational efficiency. However, there is still not enough discussion on how to effectively allocate resources in a way that is suitable for integrated services and to achieve both efficiency and responsiveness. In this study, we construct an efficient resource allocation prediction formula as a study of an efficient Many-core allocation method for edge offload. In addition, as a specific service, we decided to evaluate the offload of AI processing of communication robots. In the construction of the prediction formula, it was confirmed that sufficient processing performance and responsiveness can be obtained with the minimum core by automatically calculating the optimum number of cores from the actual application operation.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"50","bibliographic_titles":[{"bibliographic_title":"Proceedings of Asia Pacific Conference on Robot IoT System Development and Platform"}],"bibliographicPageStart":"46","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-15","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2020"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":210324,"updated":"2025-01-19T18:11:50.681040+00:00","links":{},"created":"2025-01-19T01:11:33.281335+00:00"}