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BiBTeX citation export for MOPHA032: Big Data Architectures for Logging and Monitoring Large Scale Telescope Arrays

@InProceedings{costa:icalepcs2019-mopha032,
  author       = {A. Costa and U. Becciani and P. Bruno and A.S. Calanducci and V. Conforti and F. Gianotti and A. Grillo and S. Riggi and J. Schwarz and E. Sciacca and G. Tosti and F. Vitello},
% author       = {A. Costa and U. Becciani and P. Bruno and A.S. Calanducci and V. Conforti and F. Gianotti and others},
% author       = {A. Costa and others},
  title        = {{Big Data Architectures for Logging and Monitoring Large Scale Telescope Arrays}},
  booktitle    = {Proc. ICALEPCS'19},
  pages        = {268--271},
  paper        = {MOPHA032},
  language     = {english},
  keywords     = {software, monitoring, controls, operation, database},
  venue        = {New York, NY, USA},
  series       = {International Conference on Accelerator and Large Experimental Physics Control Systems},
  number       = {17},
  publisher    = {JACoW Publishing, Geneva, Switzerland},
  month        = {08},
  year         = {2020},
  issn         = {2226-0358},
  isbn         = {978-3-95450-209-7},
  doi          = {10.18429/JACoW-ICALEPCS2019-MOPHA032},
  url          = {https://jacow.org/icalepcs2019/papers/mopha032.pdf},
  note         = {https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA032},
  abstract     = {Large volumes of technical and logging data result from the operation of large scale astrophysical infrastructures. In the last few years several "Big Data" technologies have been developed to deal with a huge amount of data, e.g. in the Internet of Things (IoT) framework. We are comparing different stacks of Big Data/IoT architectures including high performance distributed messaging systems, time series databases, streaming systems, interactive data visualization. The main aim is to classify these technologies based on a set of use cases typically related to the data produced in the astronomical environment, with the objective to have a system that can be updated, maintained and customized with a minimal programming effort. We present the preliminary results obtained, using different Big Data stack solution to manage some use cases related to quasi real-time collection, processing and storage of the technical data, logging and technical alert produced by the array of nine ASTRI telescopes that are under development by INAF as a pathfinder array for the Cherenkov astronomy in the TeV energy range.},
}