TY - JOUR
T1 - Aviation data lake
T2 - Using side information to enhance future air-ground vehicle networks
AU - Sun, Jinlong
AU - Gui, Guan
AU - Sari, Hikmet
AU - Gacanin, Haris
AU - Adachi, Fumiyuki
N1 - Funding Information:
This work was supported by the Project Funded by the Industrial Internet Innovation and Development Project of the Ministry of Industry and Information Technology of China under grant TC190A3WZ-2, the National Natural Science Foundation of China under grant 61901228, the Six Top Talents Program of Jiangsu under grant XYDXX-010, and the 1311 Talent Plan of Nanjing University of Posts and Telecommunications. The corresponding author of this article is Guan Gui.
Publisher Copyright:
© 2005-2012 IEEE.
PY - 2021/3
Y1 - 2021/3
N2 - Future denser air-ground vehicle networks (AGVNs) face challenges such as resource allocation, mobility management, secure transmission, and so on. At the same time, surveillance is a must for modern air traffic management. This motivates us to find opportunities in the aerial vertical by forming a conceptual surveillance plane for aerial vehicles. In this article, we propose an enhanced software-defined network architecture where the surveillance plane can provide local and global surveillance information to macro stations, acting as a side system for the communication links. We review air- ground communications and, by summarizing challenges and opportunities, propose the enhanced architecture of side-information-assisted networks in detail. We then present how we obtain, organize, manage, and utilize the local and global side information by a so-called aviation data lake (ADL). The data lake can be easily connected with advanced machine learning schemes and, thus, provide timely, context-aware metrics and predictions.
AB - Future denser air-ground vehicle networks (AGVNs) face challenges such as resource allocation, mobility management, secure transmission, and so on. At the same time, surveillance is a must for modern air traffic management. This motivates us to find opportunities in the aerial vertical by forming a conceptual surveillance plane for aerial vehicles. In this article, we propose an enhanced software-defined network architecture where the surveillance plane can provide local and global surveillance information to macro stations, acting as a side system for the communication links. We review air- ground communications and, by summarizing challenges and opportunities, propose the enhanced architecture of side-information-assisted networks in detail. We then present how we obtain, organize, manage, and utilize the local and global side information by a so-called aviation data lake (ADL). The data lake can be easily connected with advanced machine learning schemes and, thus, provide timely, context-aware metrics and predictions.
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U2 - 10.1109/MVT.2020.3014598
DO - 10.1109/MVT.2020.3014598
M3 - Article
AN - SCOPUS:85100898149
VL - 16
SP - 40
EP - 48
JO - IEEE Vehicular Technology Magazine
JF - IEEE Vehicular Technology Magazine
SN - 1556-6072
IS - 1
M1 - 9199550
ER -