{"created":"2024-07-10T01:41:10.966070+00:00","id":2000228,"links":{},"metadata":{"_buckets":{"deposit":"af8f0c42-f01f-4c44-8104-d36b229f1b7d"},"_deposit":{"created_by":20,"id":"2000228","owner":"20","owners":[20],"pid":{"revision_id":0,"type":"depid","value":"2000228"},"status":"published"},"_oai":{"id":"oai:muroran-it.repo.nii.ac.jp:02000228","sets":["216:316","216:352","216:461","46"]},"author_link":[],"item_79_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2022-08-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicPageEnd":"159","bibliographicPageStart":"154","bibliographicVolumeNumber":"37","bibliographic_titles":[{"bibliographic_title":"IEEE Network","bibliographic_titleLang":"en"}]}]},"item_79_description_7":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"In next-generation mobile communications, spaceair-\nground integrated networks (SAGINs) is an emerging infrastructure\nin future wireless access networks. Since artificial\nintelligence (AI) applications become more and more important,\nit is essential to build a deep learning service-oriented SAGINs.\nIn this article, we present a hierarchical intelligent computing\nstructure focusing on processing deep learning tasks in future\nSAGINs. An optimization strategy is also proposed to improve the\nquality-of-service (QoS) of deep learning tasks in the proposed\nstructure. We test our work in small testbed and simulations.\nThe evaluation results show that the proposed work outperforms\nother offloading strategies in a SAGIN environment.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_79_link_17":{"attribute_name":"出版者版へのリンク","attribute_value_mlt":[{"subitem_link_language":"en","subitem_link_text":"https://doi.org/10.1109/MNET.001.2000512","subitem_link_url":"https://doi.org/10.1109/MNET.001.2000512"}]},"item_79_publisher_11":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"IEEE","subitem_publisher_language":"en"}]},"item_79_relation_18":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"10.1109/MNET.001.2000512","subitem_relation_type_select":"DOI"}}]},"item_79_rights_19":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.","subitem_rights_language":"en"}]},"item_79_source_id_12":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"0890-8044","subitem_source_identifier_type":"PISSN"}]},"item_79_version_type_21":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorAffiliations":[{"affiliationNames":[{},{}]}],"creatorNames":[{"creatorName":"Li He","creatorNameLang":"en"},{"creatorName":"李　鶴","creatorNameLang":"ja"}],"familyNames":[{},{}],"givenNames":[{},{}]},{"creatorAffiliations":[{"affiliationNames":[{},{}]}],"creatorNames":[{"creatorName":"Ota Kaoru","creatorNameLang":"en"},{"creatorName":"太田　香","creatorNameLang":"ja"}],"familyNames":[{},{}],"givenNames":[{},{}]},{"creatorAffiliations":[{"affiliationNames":[{},{}]}],"creatorNames":[{"creatorName":"Dong Mianxiong","creatorNameLang":"en"},{"creatorName":"董　冕雄","creatorNameLang":"ja"}],"familyNames":[{},{}],"givenNames":[{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2024-07-10"}],"filename":"MNET.001.2000512.pdf","filesize":[{"value":"2.3 MB"}],"format":"application/pdf","url":{"objectType":"fulltext","url":"https://muroran-it.repo.nii.ac.jp/record/2000228/files/MNET.001.2000512.pdf"},"version_id":"73b41f36-36dc-41bf-9a53-f2cb2f8a3b48"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"AGINsAGINsS","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Deep Learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"AI","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Service-Oriented Networking","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"AI in SAGIN: Building Deep Learning Service-Oriented Space-Air-Ground Integrated Networks","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"AI in SAGIN: Building Deep Learning Service-Oriented Space-Air-Ground Integrated Networks","subitem_title_language":"en"}]},"item_type_id":"79","owner":"20","path":["46","316","352","461"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2024-07-16"},"publish_date":"2024-07-16","publish_status":"0","recid":"2000228","relation_version_is_last":true,"title":["AI in SAGIN: Building Deep Learning Service-Oriented Space-Air-Ground Integrated Networks"],"weko_creator_id":"20","weko_shared_id":-1},"updated":"2024-07-16T02:03:09.350949+00:00"}