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| Titel |
CLOUDCLOUD : general-purpose instrument monitoring and data managing software |
| VerfasserIn |
Antonio Dias, António Amorim, António Tomé |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250132864
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| Publikation (Nr.) |
 EGU/EGU2016-13410.pdf |
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| Zusammenfassung |
| \begin{document}
\title{$CLOUD{}^{CLOUD}$: general-purpose instrument monitoring and data
managing software}
\maketitle
\begin{abstract}An effective experiment is dependent on the ability to store and deliver
data and information to all participant parties regardless of their
degree of involvement in the specific parts that make the experiment
a whole. Having fast, efficient and ubiquitous access to data will
increase visibility and discussion, such that the outcome will have
already been reviewed several times, strengthening the conclusions.
The $CLOUD{}^{CLOUD}$ project aims at providing users with a general
purpose data acquisition, management and instrument monitoring platform
that is fast, easy to use, lightweight and accessible to all participants
of an experiment. This work is now implemented in the CLOUD experiment
at CERN and will be fully integrated with the experiment as of 2016.
Despite being used in an experiment of the scale of CLOUD, this software
can also be used in any size of experiment or monitoring station,
from single computers to large networks of computers to monitor any
sort of instrument output without influencing the individual instrument's
DAQ. Instrument data and meta data is stored and accessed via a specially
designed database architecture and any type of instrument output is
accepted using our continuously growing parsing application. Multiple
databases can be used to separate different data taking periods or
a single database can be used if for instance an experiment is continuous.
A simple web-based application gives the user total control over the
monitored instruments and their data, allowing data visualization
and download, upload of processed data and the ability to edit existing
instruments or add new instruments to the experiment. When in a network,
new computers are immediately recognized and added to the system and
are able to monitor instruments connected to them. Automatic computer
integration is achieved by a locally running python-based parsing
agent that communicates with a main server application guaranteeing
that all instruments assigned to that computer are monitored with
parsing intervals as fast as milliseconds. This software (server+agents+interface+database)
comes in easy and ready-to-use packages that can be installed in any
operating system, including Android and iOS systems. This software
is ideal for use in modular experiments or monitoring stations with
large variability in instruments and measuring methods or in large
collaborations, where data requires homogenization in order to be
effectively transmitted to all involved parties. This work presents
the software and provides performance comparison with previously used
monitoring systems in the CLOUD experiment at CERN.\end{abstract}
\end{document} |
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