{"created":"2023-06-19T10:29:42.551077+00:00","id":9687,"links":{},"metadata":{"_buckets":{"deposit":"915489e4-adcb-4473-bb59-40ae5dabca38"},"_deposit":{"created_by":18,"id":"9687","owners":[18],"pid":{"revision_id":0,"type":"depid","value":"9687"},"status":"published"},"_oai":{"id":"oai:muroran-it.repo.nii.ac.jp:00009687","sets":["41:227"]},"author_link":["54836"],"item_81_date_granted_17":{"attribute_name":"学位授与年月日","attribute_value_mlt":[{"subitem_dategranted":"2018-03-23"}]},"item_81_degree_grantor_10":{"attribute_name":"学位授与機関","attribute_value_mlt":[{"subitem_degreegrantor":[{"subitem_degreegrantor_language":"ja","subitem_degreegrantor_name":"室蘭工業大学"},{"subitem_degreegrantor_language":"en","subitem_degreegrantor_name":"Muroran Institute of Technology"}],"subitem_degreegrantor_identifier":[{"subitem_degreegrantor_identifier_name":"10103","subitem_degreegrantor_identifier_scheme":"kakenhi"}]}]},"item_81_degree_name_11":{"attribute_name":"学位名","attribute_value_mlt":[{"subitem_degreename":"博士（工学）","subitem_degreename_language":"ja"}]},"item_81_description_25":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_81_description_7":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Recently, there are more than 9 billion things that connected in the Internet of Things (IoT) and the number is exceed more than 24 billion in 2020. It means that numerous data will be generated because of increasing quickly of the number of things. An infrastructure should be developed to manage the connected things in IoT. Moreover, cloud computing will play important role in terms of data storage and analysis for IoT. Therefore, a cloud broker is considered as an intermediary in the infrastructure for managing the connected things. The cloud broker will find the best deal between clients and service providers. However, there are three problems among cloud broker, clients and service providers that are the response time of the request from clients, the energy consumption of the system and the profit of the cloud broker. The three problems are considered as multi-objective optimization problem to maximize the profit of the broker while minimizing the response time of the request and the energy consumption. A multi-objective particle swarm optimization (MOPSO) is proposed to solve the problem. MOPSO is compared with a non-dominated sorting genetic algorithm-II (NSGA-II) and a random search algorithm to show the performance. Since, there are a lot of data including social media and geographic location, generated in IoT. Coupling social media with geographic location has boosted the worth of understanding the real-world situations. Event detection aims to find more specific topic which represents real-world event. However,identification of unusual and seemingly inconsistent patterns in data, called outliers, is necessary. The problem is how to partition a spatio-temporal domain to find a meaningful local outlier pattern. A k-dimensional (KD) tree partitioning is applied to divide a spatio-temporal domain into sub-cells. The optimal partitioning problem in a spatio-temporal domain has been proven as an NP-complete problem. Therefore, a genetic algorithm is proposed to solve the problem. Moreover, the smart grid is strongly related to IoT technologies. It is enabled by IoT to handle big data and reduce the number of communication protocols. The micro-grid is studied because of micro-grids are part of a larger system that makes the smart grid to become reality. The operation management problem and pollutant emission problem are important problems for the micro-grid system. Thus, reducing the total energy expenses and pollutant emission of micro-grid and improving the renewable energy sources (battery energy storage) are considered together with the operation management of the micro-grid system. A fitness-based modified game particle swarm optimization (FMGPSO) algorithm is proposed to minimize the total costs of operation and pollutant emissions in the microgrid and multi-microgrid system. FMGPSO is compared with A non-dominated sorting genetic algorithm-III (NSGA-III), a multi-objective covariance matrix adaptation evolution strategy (MO-CMAES), and a speed-constrained multi-objective particle swarm optimization (SMPSO) to show the performance.","subitem_description_language":"en","subitem_description_type":"Abstract"},{"subitem_description":"最近では、Internet of Things（IoT）に接続されているものは90億件を超え、2020年には240億件を超えている。それは、物事の数が急速に増えるため、多くのデータが生成されることを意味する。IoTで接続されたものを管理するためのインフラストラクチャを開発する必要がある。さらに、クラウドコンピューティングは、IoTのデータストレージと分析の観点から重要な役割を果たしている。したがって、クラウドブローカーは、接続されたものを管理するためのインフラストラクチャの仲介者とみなされる。クラウドブローカーは、クライアントとサービスプロバイダーの間で最良の取引を見つけるだろう。しかし、クラウドブローカー、クライアントおよびサービスプロバイダーには、クライアントからの要求の応答時間、システムのエネルギー消費、クラウドブローカーのプロセスという3つの問題がある。この3つの問題は、要求の応答時間とエネルギー消費を最小限に抑えながら、ブローカーのプロビジョニングを最大化するための多目的最適化問題とみなされる。この問題を解決するために、多目的粒子群最適化（MOPSO）が提案されている。 MOPSOは、非優性選別遺伝的アルゴリズム-II（NSGA-II）およびランダム探索アルゴリズムと比較され、性能が示される。ソーシャルメディアや地理的な場所など、IoTで生成される多くのデータがあるためである。地理的な場所とソーシャルメディアを結び付けることで、現実の状況を理解する価値が高まっている。イベント検出は、実際のイベントを表すより特定のトピックを見つけることを目指している。しかし、異常値と呼ばれる異常なパターンや一見不整合なパターンの同定が必要である。問題は、時空間ドメインを分割して意味のある局所的な奇妙なパターンを見つける方法である。時空間領域をサブセルに分割するために、k次元（KD）ツリー分割が適用される。時空間領域における最適な分割問題は、NP完全な問題として証明されている。したがって、この問題を解決するための遺伝的アルゴリズムが提案されている。さらに、スマートグリッドはIoT技術と強く関連している。 IoTによって大きなデータを処理し、通信プロトコルの数を減らすことができる。マイクログリッドはスマートグリッドを現実化させるより大きなシステムの一部であるため、マイクログリッドが研究されている。運用管理上の問題や汚染物質排出問題は、マイクログリッドシステムにとって重要な問題である。したがって、マイクログリッドシステムの運用管理とともに、マイクログリッドの総エネルギー費用と汚染物質排出量の削減と再生可能エネルギー源の改善（バッテリエネルギー貯蔵）が考慮されている。マイクログリッドおよびマルチマイクログリッドシステムにおける操作および汚染物質排出の総コストを最小限に抑えるため、MGPSO アルゴリズムが提案されている。 FMGPSOは、非優先ソート遺伝的アルゴリズム-III（NSGA-III）、多目的共分散行列適応進化戦略（MO-CMAES）、および性能を示すために速度が制約された多目的粒子群最適化（SMPSO）と比較される。","subitem_description_language":"ja","subitem_description_type":"Abstract"}]},"item_81_dissertation_number_13":{"attribute_name":"学位授与番号","attribute_value_mlt":[{"subitem_dissertationnumber":"甲第418号"}]},"item_81_identifier_registration":{"attribute_name":"ID登録","attribute_value_mlt":[{"subitem_identifier_reg_text":"10.15118/00009639","subitem_identifier_reg_type":"JaLC"}]},"item_81_subject_9":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"007","subitem_subject_scheme":"NDC"}]},"item_81_text_12":{"attribute_name":"学位の種別","attribute_value_mlt":[{"subitem_text_language":"ja","subitem_text_value":"課程博士"}]},"item_81_text_14":{"attribute_name":"報告番号","attribute_value_mlt":[{"subitem_text_language":"ja","subitem_text_value":"甲第418号"}]},"item_81_text_15":{"attribute_name":"学位記番号","attribute_value_mlt":[{"subitem_text_language":"ja","subitem_text_value":"博甲第418号"}]},"item_81_text_16":{"attribute_name":"研究科・専攻","attribute_value_mlt":[{"subitem_text_language":"ja","subitem_text_value":"工学専攻・先端情報電子工学コース"}]},"item_81_version_type_24":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open 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MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"A418","objectType":"fulltext","url":"https://muroran-it.repo.nii.ac.jp/record/9687/files/A418.pdf"},"version_id":"c0fe6d7a-4d6d-40fd-a8d0-d2984f869921"},{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2018-06-06"}],"displaytype":"detail","filename":"A418_summary.pdf","filesize":[{"value":"233.2 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"A418_summary","objectType":"abstract","url":"https://muroran-it.repo.nii.ac.jp/record/9687/files/A418_summary.pdf"},"version_id":"2bdcd5dd-4ab7-4d62-9d0b-13e6d91a59ac"}]},"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":"doctoral thesis","resourceuri":"http://purl.org/coar/resource_type/c_db06"}]},"item_title":"Resource Optimization for Connected Internet of Things","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Resource Optimization for Connected Internet of Things","subitem_title_language":"en"},{"subitem_title":"IoTにおけるリソースの最適化","subitem_title_language":"ja"}]},"item_type_id":"81","owner":"18","path":["227"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2018-06-06"},"publish_date":"2018-06-06","publish_status":"0","recid":"9687","relation_version_is_last":true,"title":["Resource Optimization for Connected Internet of Things"],"weko_creator_id":"18","weko_shared_id":-1},"updated":"2024-01-22T01:33:47.135645+00:00"}