{"_buckets": {"deposit": "c4bfe433-66da-4c0b-9d69-d2f0bf2a794a"}, "_deposit": {"id": "4715", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4715"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4715", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Cloud Infrastructure Resource Demand Prediction Model Using Parameter Optimization and Feature Selection", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Cloud computing offer highly scalable, andeconomical infrastructure for promising heterogeneousplatforms and various applications. According to thegrowing demand nature of cloud infrastructureresources, the cloud providers face the challenge ofperforming the effective resource management. Thispaper presents the development of the CPU resourcedemand prediction model for cloud infrastructure toovercome the critical issue of the cloud providers forworkload forecasting and optimal resourcemanagement. The model is developed based on thepowerful machine learning technique, Random Forests(RF) algorithm via the real data center workload traces.To get the best prediction model by RF, the parameteroptimization is performed. Moreover, some features ofworkload traces cannot influence in prediction and alsogive overheads in model development time. So, thefeature selection is applied to extract the importantfeatures. The performance evaluation of the proposedmodel against four workload traces is also presented."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Cloud Computing"}, {"interim": "Feature Selection"}, {"interim": "Machine Learning"}, {"interim": "Parameter Optimization"}, {"interim": "Random Forests"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value": []}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Tenth International Conference On Computer Applications (ICCA 2012)", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Myo, Myint Myat"}, {"subitem_authors_fullname": "Thein, Thandar"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2012-02-28"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/420"}, "item_title": "Cloud Infrastructure Resource Demand Prediction Model Using Parameter Optimization and Feature Selection", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004715", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-04"}, "publish_date": "2019-07-04", "publish_status": "0", "recid": "4715", "relation": {}, "relation_version_is_last": true, "title": ["Cloud Infrastructure Resource Demand Prediction Model Using Parameter Optimization and Feature Selection"], "weko_shared_id": -1}