{"_buckets": {"deposit": "8a0a722a-8482-4ae9-b6f6-cfb37caf66de"}, "_deposit": {"id": "3535", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "3535"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/3535", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Local Disaster Recovery Using Virtualization Technology", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Business applications running on ITinfrastructure necessitate high levels of availability inorder to minimize the amount of downtimeexperienced during any planned and unplannedoutages. As a result, disaster recovery has gainedgreat significance in IT. Exploiting virtualization andability to automatically reinstall a host, where theaction on a virtual machine is performed only when adisaster occurs. Virtualization affords significant costand performance advantages over more traditionaldisaster recovery options such as tape backup orimaging. Our approach is to design and implement acontinual migration strategy for virtual machines toachieve automatic failure recovery. By continuallyand transparently propagating virtual machine’s stateto a backup host via live migration techniques, trivialapplications encapsulated in the virtual machine canbe recovered from hardware failures with minimaldowntime while no modifications are required.Moreover, our framework intends to monitor virtualmachines for problems such as CPU utilization, I/Oactivity, and memory utilization. This raises adifficult problem, since it is quite difficult todiscriminate based on these measures between avirtual object that is performing properly, and onethat is quite ill. We apply the out-of-band monitoringusing virtualization and machine learning canaccurately identify faults in the guest OS, whileavoiding the many pitfalls associated with in-bandmonitoring."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "virtualization"}, {"interim": "availability"}, {"interim": "fault-tolerance"}, {"interim": "machine learning"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-25"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "psc2010paper (75).pdf", "filesize": [{"value": "59 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 59000.0, "url": {"url": "https://meral.edu.mm/record/3535/files/psc2010paper (75).pdf"}, "version_id": "6032b5a9-e365-4f05-a1b2-b56d4cba40b3"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Fifth Local Conference on Parallel and Soft Computing", "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": "Paing, Aye Myat Myat"}]}]}, "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": "2010-12-16"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/1276"}, "item_title": "Local Disaster Recovery Using Virtualization Technology", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000003535", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-25"}, "publish_date": "2019-07-25", "publish_status": "0", "recid": "3535", "relation": {}, "relation_version_is_last": true, "title": ["Local Disaster Recovery Using Virtualization Technology"], "weko_shared_id": -1}