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2016 | OriginalPaper | Buchkapitel

Big Data Analytics Platforms for Real-Time Applications in IoT

verfasst von : Yogesh Simmhan, Srinath Perera

Erschienen in: Big Data Analytics

Verlag: Springer India

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Abstract

Big data platforms have predominantly focused on the volume aspects of large-scale data management. The growing pervasiveness of Internet of Things (IoT) applications, along with their associated ability to collect data from physical and virtual sensors continuously, highlights the importance of managing the velocity dimension of big data too. In this chapter, we motivate the analytics requirements of IoT applications using several practical use cases, characterize the trade-offs between processing latency and data volume capacity of contemporary big data platforms, and discuss the critical role that Distributed Stream Processing and Complex Event Processing systems play in addressing the analytics needs of IoT applications.

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Vorheriges Kapitel Online Graph Partitioning with an Affine Message Combining Cost Function

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Titel: Big Data Analytics Platforms for Real-Time Applications in IoT
verfasst von: Yogesh Simmhan
Srinath Perera
Verlag: Springer India
Buch: Big Data Analytics
Print ISBN: 978-81-322-3626-9

Electronic ISBN: 978-81-322-3628-3

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-81-322-3628-3_7

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