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Scalable and flexible middleware for dynamic data flows

Boomker, S. (2016) Scalable and flexible middleware for dynamic data flows. Master's Thesis / Essay, Computing Science.

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Due to the concepts of Internet of Things and Big data, the traditional client-server architecture is not sufficient any more. One of the main reasons is wide range of expanding heterogeneous applications, data sources and environments. New forms of data processing require new architectures and techniques in order to be scalable, flexible and able to handle fast dynamic data flows. The backbone of all those objects, applications and users is called the middleware. This research goes about designing and implementing a middleware by taking into account different state of the art tools and techniques. To come up to a solution which is able to handle a flexible set of sources and models across organizational borders. At the same time it is de-centralized, distributed and, although de-central able to perform semantic based system integration centrally. This is accomplished by introducing of an architecture containing a combination of data integration patterns, semantic storage and stream processing patterns. A reference implementation is presented of the proposed architecture based on Apache Camel framework. This prototype provides the ability to dynamically create and change flexible and distributed data flows during runtime. The implementation is evaluated in terms of scalability, fault tolerance and flexibility.

Item Type: Thesis (Master's Thesis / Essay)
Degree programme: Computing Science
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 08:25
Last Modified: 15 Feb 2018 08:25

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