Towards a Big Data Platform for Managing Machine Generated Data in the Cloud

Nicolas Ferry, German Terrazas, Per Kalweit, Arnor Solberg, Svetan Ratchev, Dirk Weinelt

Sintef, University of Nottingham, Tagueri

proceedings of the IEEE 15th International Confetrence of Industrial Informatics (INDIN), pages 263-270

DOI 10.1109/INDIN.2017.8104782



Presentation at the Conference INDIN2017 by partners Sintef, University of Nottingham and Tagueri.

Hereafter the abstract:

"Industry 4.0 proposes the integration of the new generation of ICT solutions for the monitoring, adaptation, simulation, and optimisation of factories.
With the democratization of sensors and actuators, factories and machine tools can now be sensorized and the data generated by these devices can be exploited, for instance, to optimize the utilization of the machines as well as their operation and maintenance. However, analyzing the vast amount of data generated is resource demanding both in term of computing power and network bandwidth, thus requiring highly scalable solutions. This paper presents a novel big data platform for the management of machine generated data in the cloud. It brings together standard open source technologies which can be adapted to and deployed on different cloud infrastructures, hence reducing costs, minimising deployment difficulty and providing ondemand access to a virtually infinite set of computing, storage and network resources."

Last modified on Thursday, 26 April 2018 17:37
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