{"_buckets": {"deposit": "84b9283f-0650-4503-aca0-6e8d7bf0c352"}, "_deposit": {"id": "4516", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4516"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4516", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Analyzing Fuzzy Models for VM Resource Usage Prediction in Virtualized Data Center", "subitem_1551255648112": "en_US"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Data Centre (DC) administrators try todelivering performance guarantees whilemanaging resources for utilization in terms ofreducing cost. With the advent of serverconsolidation provided by virtualizationtechnology, multiple heterogeneous virtualmachines (VMs) can be coexisted on a physicalserver and shared resources together. Fixedallocation of resources to VMs is not the optimalallocation method as over provisioning andunder provisioning can be caused. For dynamicallocation, simultaneous on demand provisioningof shared physical resources to VMs becomes thekey challenge.This paper proposes resource usageprediction system by making analysis on theaccuracy of three different models; Fuzzymodeling, adaptive Fuzzy modeling and NeuroFuzzy modeling. To evaluate the efficiency ofthree different models, experiments are carriedout by workload-resource mapping andresource-resource mapping approaches. CPUprofiles from real world data centre are used toanalyze through a simulating program.Experimental results show that the proposedresource prediction models can predict well nexttime interval resource usage of virtual machineeven in the condition of unexpected high spikesCPU."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "resource prediciton"}, {"interim": "virtualized data center"}, {"interim": "resource provisioning"}, {"interim": "fuzzy"}, {"interim": "adaptive fuzzy"}, {"interim": "neuro-fuzzy"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-11-15"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "10097.pdf", "filesize": [{"value": "557 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 557000.0, "url": {"url": "https://meral.edu.mm/record/4516/files/10097.pdf"}, "version_id": "6b585b97-97d0-4c99-baeb-3e6589f3ff27"}]}, "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": "Sithu, Mya"}]}]}, "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/123456789/2441"}, "item_title": "Analyzing Fuzzy Models for VM Resource Usage Prediction in Virtualized Data Center", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004516", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-11-15"}, "publish_date": "2019-11-15", "publish_status": "0", "recid": "4516", "relation": {}, "relation_version_is_last": true, "title": ["Analyzing Fuzzy Models for VM Resource Usage Prediction in Virtualized Data Center"], "weko_shared_id": -1}