Automating Cloud Services Lifecycle through Semantic technologies

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dc.contributor.authorJoshi, Karuna Pande
dc.contributor.authorYesha, Yelena
dc.contributor.authorFinin, Tim
dc.date.accessioned2018-11-06T17:15:46Z
dc.date.available2018-11-06T17:15:46Z
dc.date.issued2014-01-01
dc.description2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)en_US
dc.description.abstractManaging virtualized services efficiently over the cloud is an open challenge. Traditional models of software development are not appropriate for the cloud computing domain, where software (and other) services are acquired on demand. In this paper, we describe a new integrated methodology for the lifecycle of IT services delivered on the cloud, and demonstrate how it can be used to represent and reason about services and service requirements and so automate service acquisition and consumption from the cloud. We have divided the IT service lifecycle into five phases of requirements, discovery, negotiation, composition, and consumption. We detail each phase and describe the ontologies that we have developed to represent the concepts and relationships for each phase. To show how this lifecycle can automate the usage of cloud services, we describe a cloud storage prototype that we have developed. This methodology complements previous work on ontologies for service descriptions in that it is focused on supporting negotiation for the particulars of a service and going beyond simple matchmaking.en_US
dc.description.urihttps://ieeexplore.ieee.org/document/8366975en_US
dc.format.extent14 pagesen_US
dc.genreconference papers and proceedings pre-printen_US
dc.identifierdoi:10.13016/M2CF9JB02
dc.identifier.citationKaruna Pande Joshi, Yelena Yesha, and Tim Finin, Automating Cloud Services Lifecycle through Semantic technologies, IEEE Transactions on Service Computing, DOI: 10.1109/IoTDI.2018.00014en_US
dc.identifier.uri10.1109/IoTDI.2018.00014
dc.identifier.urihttp://hdl.handle.net/11603/11891
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rights© 2018 IEEE
dc.subjectActivity recognitionen_US
dc.subjectTarget recognitionen_US
dc.subjectComputational modelingen_US
dc.subjectAdaptation modelsen_US
dc.subjectMachine learningen_US
dc.subjecttransfer learningen_US
dc.subjectAutoencoder based ARen_US
dc.subjectHuman Activity Recognitionen_US
dc.subjectAccelerometer Sensoren_US
dc.subjectWearable Computingen_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleAutomating Cloud Services Lifecycle through Semantic technologiesen_US
dc.typeTexten_US

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