{"created":"2023-06-19T10:30:10.830914+00:00","id":10380,"links":{},"metadata":{"_buckets":{"deposit":"708d33cb-f7c8-4e92-860e-68a46e55017b"},"_deposit":{"created_by":18,"id":"10380","owners":[18],"pid":{"revision_id":0,"type":"depid","value":"10380"},"status":"published"},"_oai":{"id":"oai:muroran-it.repo.nii.ac.jp:00010380","sets":["216:316","216:352","46"]},"author_link":["21131","58256","39157"],"item_79_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2020","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicPageEnd":"435","bibliographicPageStart":"428","bibliographicVolumeNumber":"6","bibliographic_titles":[{"bibliographic_title":"IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING","bibliographic_titleLang":"en"}]}]},"item_79_description_23":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_79_description_7":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Recently, the installation of 5G networks offers a variety of real-time, high-performance and human-oriented customized services. However, the current laying 5G structure is unable to meet all of the growing communication needs by these new emerging services. In this paper, we propose a DQL (Deep Q-learning Network) based intelligent resource management method for 5G architecture, to improve the quality of service (QoS) under limited communication resources. In the environment of network function virtualization (NFV), we aim at improving the efficient usage of spectrum resources. In this two-step solution, our first goal is to guarantee the maximum communication quality with the smallest number of infrastructures. Then, a DQL-based wireless resource allocation algorithm is designed to realize the elaborate operation. Unlike previous studies, our system can provide the allocation policy in a more subdivided way and finally maximize the usage of bandwidth resources. The simulation also shows that our proposed MSIO improves 3.12% in the performance of the maximum coverage importance problem and the ARODQ algorithm improves 4.05% than other standard solutions.","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_text":"10.1109/TCCN.2020.2982886","subitem_link_url":"https://doi.org/10.1109/TCCN.2020.2982886"}]},"item_79_link_5":{"attribute_name":"室蘭工業大学研究者データベースへのリンク","attribute_value_mlt":[{"subitem_link_text":"董 冕雄（DONG Mianxiong）","subitem_link_url":"http://rdsoran.muroran-it.ac.jp/html/100000145_ja.html"},{"subitem_link_text":"太田 香（OTA Kaoru）","subitem_link_url":"http://rdsoran.muroran-it.ac.jp/html/100000140_ja.html"}]},"item_79_publisher_11":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC","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/TCCN.2020.2982886","subitem_relation_type_select":"DOI"}}]},"item_79_rights_19":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"© 2020 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":"2332-7731","subitem_source_identifier_type":"EISSN"}]},"item_79_subject_9":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"007","subitem_subject_scheme":"NDC"}]},"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":[{"creatorNames":[{"creatorName":"ZHANG, Chaofeng","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{}],"affiliationNames":[{},{}]}],"creatorNames":[{"creatorName":"DONG,  Mianxiong","creatorNameLang":"en"},{"creatorName":"トウ, メンユウ","creatorNameLang":"ja-Kana"},{"creatorName":"董, 冕雄","creatorNameLang":"ja"}],"familyNames":[{},{},{}],"givenNames":[{},{},{}],"nameIdentifiers":[{},{}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{}],"affiliationNames":[{},{}]}],"creatorNames":[{"creatorName":"OTA,  Kaoru","creatorNameLang":"en"},{"creatorName":"太田, 香","creatorNameLang":"ja"},{"creatorName":"オオタ, カオル","creatorNameLang":"ja-Kana"}],"familyNames":[{},{},{}],"givenNames":[{},{},{}],"nameIdentifiers":[{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2020-12-08"}],"displaytype":"detail","filename":"IEEETCCA_6_2_428_435.pdf","filesize":[{"value":"1.8 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"IEEETCCA_6_2_428_435","objectType":"fulltext","url":"https://muroran-it.repo.nii.ac.jp/record/10380/files/IEEETCCA_6_2_428_435.pdf"},"version_id":"e4bbe345-9137-4557-9f3a-e3e74ccffa06"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Intelligent control","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"intelligent networks","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"artificial intelligence","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"management decision-making","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"mobile communication","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":"Fine-Grained Management in 5G: DQL Based Intelligent Resource Allocation for Network Function Virtualization in C-RAN","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Fine-Grained Management in 5G: DQL Based Intelligent Resource Allocation for Network Function Virtualization in C-RAN","subitem_title_language":"en"}]},"item_type_id":"79","owner":"18","path":["46","316","352"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2020-12-08"},"publish_date":"2020-12-08","publish_status":"0","recid":"10380","relation_version_is_last":true,"title":["Fine-Grained Management in 5G: DQL Based Intelligent Resource Allocation for Network Function Virtualization in C-RAN"],"weko_creator_id":"18","weko_shared_id":-1},"updated":"2023-10-24T01:52:43.152182+00:00"}