Semantically Rich Framework to Automate KnowledgeExtraction from Cloud Service Level Agreement

dc.contributor.advisorJoshi, Karuna Pande
dc.contributor.authorNatolana Ganapathy, Divya
dc.contributor.departmentComputer Science and Electrical Engineering
dc.contributor.programComputer Science
dc.date.accessioned2021-09-01T13:55:49Z
dc.date.available2021-09-01T13:55:49Z
dc.date.issued2020-01-01
dc.description.abstractConsumers evaluate the performance of their cloud-based services by monitoring the Service Level Agreements (SLA) that list the service terms and metrics agreed with the service providers. Current Cloud SLAs are documents that require significant manual effort to parse and determine if providers meet the SLAs. Moreover, due to the lack of standardization, providers differ in the way they define the terms and metrics, making it more difficult to ensure continuous SLA monitoring. We have developed a novel framework to significantly automate the process of extracting knowledge embedded in cloud SLAs and representing it in a semantically rich Ontology. Our framework captures the key terms, standards,remedies for noncompliance and roles and responsibilities, in the form of deontic statements and their actors from cloud SLAs. Its mostly built on major cloud SLAs, but could be adapted to other domains as well. In this theses `Semantically rich framework to automate knowledge extraction from cloud SLA' , we discuss the challenges in automating cloud services management and how we address these with our framework.
dc.formatapplication:pdf
dc.genretheses
dc.identifierdoi:10.13016/m2qhfx-jjem
dc.identifier.other12168
dc.identifier.urihttp://hdl.handle.net/11603/22901
dc.languageen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Theses and Dissertations Collection
dc.relation.ispartofUMBC Graduate School Collection
dc.relation.ispartofUMBC Student Collection
dc.sourceOriginal File Name: NatolanaGanapathy_umbc_0434M_12168.pdf
dc.subjectActor Extraction
dc.subjectDeontic Statements
dc.subjectNatural Lanaguage Processing
dc.subjectOntology
dc.subjectSemantic Web
dc.subjectSPARQL Query
dc.titleSemantically Rich Framework to Automate KnowledgeExtraction from Cloud Service Level Agreement
dc.typeText
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