{"_buckets": {"deposit": "19eaef79-b829-43e5-85fd-c1a68637720a"}, "_deposit": {"id": "3865", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "3865"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/3865", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Elastic Resource Prediction for Cloud Data Center", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Cloud data centers offer utility-oriented ITservices to users worldwide. The nature ofresource demand of cloud data centers is elasticas the overall workloads are always changing.For handling dynamic workload nature ahead ofthe needs, elastic resource demand prediction isthe key issue in cloud data centers. If the cloudprovider does not ensure they have enoughresources to meet demand which will lead tounder or over provisioning of resources. In thispaper, integrated elastic resource predictionsystem is proposed by combining signaturebasedprediction and state-based predictionapproahces. The workload nature of the clouddata centers are both repeating pattern and nonrepeatingpattern workload. Signature-basedprediction is used to predict the repeatingpattern workload and state-based prediction isused to predict the non-repeating patternworkload. Integrated Elastic ResourcePrediction (IERP) system is used to predict themixed workload pattern. Feature selection isconducted first to reduce processing overheadswhile achieving high prediction accuracy. Theproposed predictors are implemented andevaluated with real world workload traces whichshow that they achieve high resource prediction accuracy with above 95%."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Cloud Data Center"}, {"interim": "Integrated Elastic Resource Prediction"}, {"interim": "Signature-based Prediction"}, {"interim": "State-based Prediction"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-03"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "12059.pdf", "filesize": [{"value": "1076 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 1076000.0, "url": {"url": "https://meral.edu.mm/record/3865/files/12059.pdf"}, "version_id": "22b067ce-1c78-4eb5-924e-6fcd76dbb74b"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Twelfth International Conference On Computer Applications (ICCA 2014)", "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": "Tun, Thant Zin"}, {"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": "2014-02-17"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/159"}, "item_title": "Elastic Resource Prediction for Cloud Data Center", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000003865", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-03"}, "publish_date": "2019-07-03", "publish_status": "0", "recid": "3865", "relation": {}, "relation_version_is_last": true, "title": ["Elastic Resource Prediction for Cloud Data Center"], "weko_shared_id": -1}