The present and future data management requirements for fusion experiments are presented along with the currently adopted solutions. Even if the presented solution fulfil the requirements of the current experiments, the next generation fusion devices are likely to produce/require an unpreceded amount of data. For this reason, the solutions adopted nowadays, and also foreseen for the experiments under construction, might prove not enough scalable. Information Technology already provides efficient solutions for big data management, successfully employed for large cloud applications and social media. In particular, MongoDB, Cassandra and Hadoop represent promising candidates for the next generation experiments because their combined usage covers the specific data requirements for fusion research.

Big data requirements in current and next fusion research experiments

Manduchi G;Luchetta A;Taliercio C;
2018

Abstract

The present and future data management requirements for fusion experiments are presented along with the currently adopted solutions. Even if the presented solution fulfil the requirements of the current experiments, the next generation fusion devices are likely to produce/require an unpreceded amount of data. For this reason, the solutions adopted nowadays, and also foreseen for the experiments under construction, might prove not enough scalable. Information Technology already provides efficient solutions for big data management, successfully employed for large cloud applications and social media. In particular, MongoDB, Cassandra and Hadoop represent promising candidates for the next generation experiments because their combined usage covers the specific data requirements for fusion research.
2018
Istituto gas ionizzati - IGI - Sede Padova
Inglese
2018 IEEE International Symposium on Circuits and Systems (ISCAS)
IEEE International Symposium on Circuits and Systems 2018 (ISCAS 2018)
1
5
5
978-1-5386-4881-0
https://ieeexplore.ieee.org/document/8351712/
27-30 May 2018
Florence, Italy
Big Data
Nuclear Fusion Experiment
Data Acquisition
Databases
Print ISSN on Demand (PoD): 2379-4461 / Electronic ISBN: 978-1-5386-4881-0 Print (PoD) ISBN: 978-1-5386-4882-7
3
none
Manduchi G.; Luchetta A.; Taliercio C.; Rigoni A.
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
   Implementation of activities described in the Roadmap to Fusion during Horizon 2020 through a Joint programme of the members of the EUROfusion consortium
   EUROfusion
   H2020
   633053
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/370801
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