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Abstract
Web 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.