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2018 | OriginalPaper | Buchkapitel

Vs-Driven Big Data Process Development

verfasst von : Rustem Dautov, Salvatore Distefano

Erschienen in: New Frontiers in Quantitative Methods in Informatics

Verlag: Springer International Publishing

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Abstract

Big Data solutions aim to cope with the overwhelming amount of data generated by various domains, such as social networks and the Internet of Things, thereby enabling a new generation of data-intensive applications (DIAs) and services. At the same time, to facilitate DIA design and development processes and address (Big) data management requirements, proper techniques and tools are requested. To this purpose, this paper proposes an approach, which takes into account the established Big Data V-attributes, (i.e. Volume, Velocity, and Variety) to model and predict computational demands at design time. To do so, the approach relies on annotating Big Data process workflows (and their individual elements) with relevant V-attribute values, which are then mapped into resource requirements and used in a performance model.

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Nächstes Kapitel Capacity Planning of Fog Computing Infrastructures for Smart Monitoring

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Titel: Vs-Driven Big Data Process Development
verfasst von: Rustem Dautov
Salvatore Distefano
Verlag: Springer International Publishing
Buch: New Frontiers in Quantitative Methods in Informatics
Print ISBN: 978-3-319-91631-6

Electronic ISBN: 978-3-319-91632-3

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-91632-3_5

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