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dc.contributor.authorAl-Haj Hassan, Osama Mohammd
dc.date.accessioned2014-03-04T18:54:59Z
dc.date.available2014-03-04T18:54:59Z
dc.date.issued2010-08
dc.identifier.otheral-haj-hassan_osama_m_201008_phd
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/al-haj-hassan_osama_m_201008_phd
dc.identifier.urihttp://hdl.handle.net/10724/26551
dc.description.abstractWeb 2.0 has been growing at a rapid pace empowering end-users with a vast set of applications dedicated to improve their experience while using the Web. This improvement comes in the shape of increased personalization that enables the end users to navigate and search the Web based on their own needs. One of the key icons of Web 2.0 applications is mashups; they are essentially Web services that are often created by end-users. They aggregate and manipulate data from sources around the World Wide Web. Surprisingly, research related to mashups performance received little attention in research community. In this dissertation, we provide architectures, protocols, and schemes to enhance mashups performance and scalability. We provide improvement over mashup execution by defining a protocol and a set of rules that change the ordinary mashup execution paradigm. Further, we design caching protocol to utilize data reusability in mashups which results in more efficient mashup execution. Moreover, we propose a distributed mashup architecture which increases the scalability of mashup platforms. All the former techniques and protocols are backed up with a set of experiments proving their effectiveness in transforming mashup execution to a more efficient and scalable process.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectWeb services
dc.subjectMashup
dc.subjectPersonalization
dc.subjectData reuse
dc.subjectWeb 2.0
dc.subjectFeeds
dc.subjectCaching
dc.subjectIndexing
dc.subjectDistributed
dc.subjectPerformance
dc.subjectScalability
dc.titleScalability and efficiency in personalized Web services
dc.typeDissertation
dc.description.degreePhD
dc.description.departmentComputer Science
dc.description.majorComputer Science
dc.description.advisorLakshmish Ramaswamy
dc.description.advisorJohn A. Miller
dc.description.committeeLakshmish Ramaswamy
dc.description.committeeJohn A. Miller
dc.description.committeeThiab R. Taha
dc.description.committeeMaria Hybinette


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