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Automating the Adaptation of Evolving Data-Intensive Ecosystems

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Conceptual Modeling (ER 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8217))

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Abstract

Data-intensive ecosystems are conglomerations of data repositories surrounded by applications that depend on them for their operation. To support the graceful evolution of the ecosystem’s components we annotate them with policies for their response to evolutionary events. In this paper, we provide a method for the adaptation of ecosystems based on three algorithms that (i) assess the impact of a change, (ii) compute the need of different variants of an ecosystem’s components, depending on policy conflicts, and (iii) rewrite the modules to adapt to the change.

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Manousis, P., Vassiliadis, P., Papastefanatos, G. (2013). Automating the Adaptation of Evolving Data-Intensive Ecosystems. In: Ng, W., Storey, V.C., Trujillo, J.C. (eds) Conceptual Modeling. ER 2013. Lecture Notes in Computer Science, vol 8217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41924-9_17

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  • DOI: https://doi.org/10.1007/978-3-642-41924-9_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41923-2

  • Online ISBN: 978-3-642-41924-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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