Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/221296
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dc.date.accessioned2018-11-22T04:54:38Z-
dc.date.available2018-11-22T04:54:38Z-
dc.identifier.urihttp://hdl.handle.net/10603/221296-
dc.description.abstractDistributed systems, or distributed computing, has spawned many familiar technologies across the years, including Grid Computing, Utility Computing, Cloud Computing, application service provision (ASP) andWeb 2.0. Among these, Cloud Computing is a specialized form in which the underlying resources, such as storage, processors, and memory, are completely abstracted from the consumer. It has emerged as a paradigm to provide on demand resources to the customers, which may include access to infrastructure / application services on a subscription basis. Cloud Service Provider (CSP) facilitates many types of services among which Infrastructure as a Service (IaaS), Software as a Service (SaaS) and Platform as a Service (PaaS) are the basic types. Consumers utilize these services to simplify application utilization, store, share, and protect content. The number of CSPs who offer computing as a utility has increased rapidly in the recent years providing more options for the customers to choose from. This rapid growth of public cloud offerings allows the customers to interact with unknown service providers to carry out tasks or transactions. In such a scenario, a rating or a ranking system could help them to choose between the services as per their requirement. If an appropriate service provider is not selected, serious problems such as low-quality services and service nonfulfillment may occur. Therefore service levels of different CSPs need to be evaluated in an objective way to ensure quality, reliability and security of an application. The evaluation and selection of cloud service is a multi-criteria problem, which includes many intangible factors that are difficult to measure. For example, choice of service provider based on infrastructure facilities would be governed by a number of factors like cost, location of the server, reliability, level of security, storage availability, easeness etc..
dc.format.extentXVI, 174
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleHierarchical trust estimation framework for infrastructure based cloud service selection using fuzzy Multi objective optimization methods
dc.title.alternative
dc.creator.researcherSupriya M
dc.subject.keywordCloud computing
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideSangeeta. K, Gopal Krishna Patra
dc.publisher.placeCoimbatore
dc.publisher.universityAmrita Vishwa Vidyapeetham (University)
dc.publisher.institutionDepartment of Computer Science and Engineering
dc.date.registered1-5-2013
dc.date.completed
dc.date.awarded05/2017
dc.format.dimensions
dc.format.accompanyingmaterialCD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science and Engineering (Amrita School of Engineering)

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02_dedicated.pdf19.85 kBAdobe PDFView/Open
03_certificate.pdf170.15 kBAdobe PDFView/Open
04_declaration.pdf43.81 kBAdobe PDFView/Open
05_acknowledgements.pdf46.62 kBAdobe PDFView/Open
06_contents.pdf47.91 kBAdobe PDFView/Open
07_list of figures.pdf45.41 kBAdobe PDFView/Open
08_list of tables.pdf45.74 kBAdobe PDFView/Open
09_chapter 1.pdf1.51 MBAdobe PDFView/Open
10_chapter 2.pdf1.42 MBAdobe PDFView/Open
11_chapter 3.pdf2.56 MBAdobe PDFView/Open
12_chapter 4.pdf1.56 MBAdobe PDFView/Open
13_chapter 5.pdf452.05 kBAdobe PDFView/Open
14_chapter 6.pdf121.71 kBAdobe PDFView/Open
15_references.pdf94.6 kBAdobe PDFView/Open
16_publications.pdf63.8 kBAdobe PDFView/Open


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