Unmanned aerial vehicles optimal airtime estimation for energy aware deployment in IoT-enabled fifth generation cellular networks

[EN] Cellular networks based on new generation standards are the major enabler for Internet of things (IoT) communication. Narrowband-IoT and Long Term Evolution for Machines are the newest wide area network-based cellular technologies for IoT applications. The deployment of unmanned aerial vehicles (UAVs) has gained the popularity in cellular networks by using temporary ubiquitous coverage in the areas where the infrastructure-based networks are either not available or have vanished due to some disasters. The major challenge in such networks is the efficient UAVs deployment that covers maximum users and area with the minimum number of UAVs. The performance and sustainability of UAVs is largely dependent upon the available residual energy especially in mission planning. Although energy harvesting techniques and efficient storage units are available, but these have their own constraints and the limited onboard energy still severely hinders the practical realization of UAVs. This paper employs neglected parameters of UAVs energy consumption in order to get actual status of available energy and proposed a solution that more accurately estimates the UAVs operational airtime. The proposed model is evaluated in test bed and simulation environment where the results show the consideration of such explicit usage parameters achieves significant improvement in airtime estimation. The research is funded by the Department of Computer Science, Iqra University, Islamabad Campus, Pakistan Majeed, S.; Sohail, A.; Qureshi, KN.; Kumar, A.; Iqbal, S.; Lloret, J. (2020). Unmanned aerial vehicles optimal airtime estimation for energy aware deployment in IoT-enabled fifth generation cellular networks. EURASIP Journal on Wireless Communications and Networking. 2020(1):1-14. https://doi.org/10.1186/s13638-020-01877-0 K. Kumar, S. Kumar, O. Kaiwartya, A. Sikandar, R. Kharel, J.L. Mauri, Internet of unmanned aerial vehicles: QoS provisioning in aerial ad-hoc networks. Sensors 20(11), 3160 (2020) M. Marchese, A. Moheddine, F. Patrone, IoT and UAV integration in 5G hybrid terrestrial-satellite networks. Sensors 19(17), 3704 (2019) K. Kumar, S. Kumar, O. Kaiwartya, P.K. Kashyap, J. Lloret, H. Song, Drone assisted flying ad-hoc networks: mobility and service oriented modeling using neuro-fuzzy. Ad Hoc Netw. 102242 (2020) X. Li, Deployment of drone base stations for cellular communication without apriori user distribution information, in 2018 37th Chinese Control Conference (CCC) (IEEE,