Towards a Scalable Architecture for Flight Data Management

Iván García, Miguel A. Martínez-Prieto, Anibal Bregón, Pedro C. Álvarez, Fernando Díaz

Abstract

The dramatic growth in the air traffic levels witnessed during the last two decades has increased the interest for optimizing the Air Traffic Management (ATM) systems. The main objective is being able to cope with the sustained air traffic growth under safe, economic, efficient and environmental friendly working conditions. The ADS-B (Automatic Dependent Surveillance - Broadcast) system is part of the new air traffic control systems, since it allows to substitute the secondary radar with cheaper ground stations that, at the same time, provide more accurate real-time positioning information. However, this system generates a large volume of data that, when combined with other flight-related data, such as flight plans or weather reports, faces scalability issues. This paper introduces an (on-going) Data Lake based architecture which allows the full ADS-B data life-cycle to be supported in a scalable and cost-effective way using technologies from the Apache Hadoop ecosystem.

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Paper Citation


in Harvard Style

García I., Martínez-Prieto M., Bregón A., Álvarez P. and Díaz F. (2017). Towards a Scalable Architecture for Flight Data Management . In Proceedings of the 6th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-255-4, pages 263-268. DOI: 10.5220/0006473402630268


in Bibtex Style

@conference{data17,
author={Iván García and Miguel A. Martínez-Prieto and Anibal Bregón and Pedro C. Álvarez and Fernando Díaz},
title={Towards a Scalable Architecture for Flight Data Management},
booktitle={Proceedings of the 6th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2017},
pages={263-268},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006473402630268},
isbn={978-989-758-255-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Towards a Scalable Architecture for Flight Data Management
SN - 978-989-758-255-4
AU - García I.
AU - Martínez-Prieto M.
AU - Bregón A.
AU - Álvarez P.
AU - Díaz F.
PY - 2017
SP - 263
EP - 268
DO - 10.5220/0006473402630268