ECaD: Energy‐efficient routing in flying ad hoc networks. (21st August 2019) - Oubbati, Omar Sami; Mozaffari, Mohammad; Chaib, Noureddine; Lorenz, Pascal; Atiquzzaman, Mohammed; Jamalipour, Abbas
Summary: Much progress can be expected in the domain of unmanned aerial vehicle (UAV) communication by the next decade. The cooperation between multiple UAVs in the air exchanging data among themselves can naturally form a flying ad hoc network (FANET). Such networks can be the key support to accomplish several kinds of missions while providing the required assistance to terrestrial networks. However, they are confronted with many challenges and difficulties, which are due to the high mobility of UAVs, the frequent packet losses, and the weak links between UAVs, all affecting the reliability of the data delivery. Furthermore, the unbalanced energy consumption may result in earlier UAV failure and consequently accelerate the decrease of the network lifetime, thus disrupting the overall network. This paper supports the use of the movement information and the residual energy level of each UAV to guarantee a high level of communication stability while predicting a sudden link breakage prior to its occurrence. A robust route discovery process is used to explore routing paths where the balanced energy consumption, the link breakage prediction, and the connectivity degree of the discovered paths are all considered. The performance of the scheme is evaluated through a series of simulations. The outcomes demonstrate the benefits of the proposed scheme in terms of increasing the lifetime of the network, minimizing the number of path failures, and decreasing the packet losses. Abstract : In this paper, we report on a study with the aim to design an efficient routing solution for Flying Ad hoc Networks (FANETs) achieving a trade‐off between the balanced energy consumption among Unmanned Aerial Vehicles (UAVs) and the shortest end‐to‐end delay. Moreover, the combination of the latter trade‐off and the connectivity awareness allows to both predict routing failures prior to their occurrence and take the appropriate routing decisions in order to avoid the packet losses.