TY - JOUR
T1 - AirNet
T2 - Energy-Aware Deployment and Scheduling of Aerial Networks
AU - Bozkaya, Elif
AU - Foerster, Klaus Tycho
AU - Schmid, Stefan
AU - Canberk, Berk
N1 - Publisher Copyright:
© 1967-2012 IEEE.
PY - 2020/10
Y1 - 2020/10
N2 - Aerial Base Stations (ABSs) promise resilient and perpetual connectivity after unexpected events such as natural disasters. However, the deployment and scheduling of ABSs introduce several algorithmic challenges. In particular, on-demand communication can change over time and be hard to accurately predict, so it needs to be handled in an online manner, accounting also for battery consumption constraints. This paper presents {AirNet}, an efficient software-based solution to operate ABSs which meet these requirements. {AirNet} is based on an efficient placement algorithm for ABSs which maximizes the number of covered users, and a scheduler which navigates and recharges ABSs in an energy-aware manner. To this end, we propose an energy-aware deployment algorithm and use an energy model to analyze the power consumption and thereby, improve the flight endurance. In addition, we evaluate a novel scheduling mechanism that efficiently manages the ABSs' operations. Our simulations indicate that our approach can significantly improve the flight endurance and user coverage compared to a recent state-of-the-art approach.
AB - Aerial Base Stations (ABSs) promise resilient and perpetual connectivity after unexpected events such as natural disasters. However, the deployment and scheduling of ABSs introduce several algorithmic challenges. In particular, on-demand communication can change over time and be hard to accurately predict, so it needs to be handled in an online manner, accounting also for battery consumption constraints. This paper presents {AirNet}, an efficient software-based solution to operate ABSs which meet these requirements. {AirNet} is based on an efficient placement algorithm for ABSs which maximizes the number of covered users, and a scheduler which navigates and recharges ABSs in an energy-aware manner. To this end, we propose an energy-aware deployment algorithm and use an energy model to analyze the power consumption and thereby, improve the flight endurance. In addition, we evaluate a novel scheduling mechanism that efficiently manages the ABSs' operations. Our simulations indicate that our approach can significantly improve the flight endurance and user coverage compared to a recent state-of-the-art approach.
KW - Aerial base stations
KW - demand-aware deployment
KW - endurance
KW - energy efficiency
KW - hover time
UR - http://www.scopus.com/inward/record.url?scp=85094928003&partnerID=8YFLogxK
U2 - 10.1109/TVT.2020.3019918
DO - 10.1109/TVT.2020.3019918
M3 - Article
AN - SCOPUS:85094928003
SN - 0018-9545
VL - 69
SP - 12252
EP - 12263
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 10
M1 - 9178963
ER -