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

handle: 10251/189096
AbstractCellular 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.
- Polytechnic University Valencia (UPV) Spain
- Bahria University Pakistan
- Polytechnic University Valencia (UPV) Spain
- Universitat Politècnica de València Spain
- Galgotias University India
TK7800-8360, Computer Networks and Communications, UAV, Unmanned Aerial Vehicle Communications, Wireless Energy Harvesting and Information Transfer, Aerospace Engineering, FOS: Mechanical engineering, TK5101-6720, Dynamic deployment, Communicational energy, Cellular network, Real-time computing, Engineering, FOS: Electrical engineering, electronic engineering, information engineering, Genetics, Software deployment, Electrical and Electronic Engineering, Drone Applications, UE, Biology, Computer network, Ecology, INGENIERIA TELEMATICA, Computer science, Drone, Distributed computing, Energy aware, Energy consumption, Operating system, Energy efficiency, FOS: Biological sciences, Physical Sciences, Delay-Tolerant Networking in Mobile Ad Hoc Networks, Computer Science, Telecommunication, UAV Networks, Opportunistic Routing, Electronics
TK7800-8360, Computer Networks and Communications, UAV, Unmanned Aerial Vehicle Communications, Wireless Energy Harvesting and Information Transfer, Aerospace Engineering, FOS: Mechanical engineering, TK5101-6720, Dynamic deployment, Communicational energy, Cellular network, Real-time computing, Engineering, FOS: Electrical engineering, electronic engineering, information engineering, Genetics, Software deployment, Electrical and Electronic Engineering, Drone Applications, UE, Biology, Computer network, Ecology, INGENIERIA TELEMATICA, Computer science, Drone, Distributed computing, Energy aware, Energy consumption, Operating system, Energy efficiency, FOS: Biological sciences, Physical Sciences, Delay-Tolerant Networking in Mobile Ad Hoc Networks, Computer Science, Telecommunication, UAV Networks, Opportunistic Routing, Electronics
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).8 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10% visibility views 39 download downloads 49 - 39views49downloads
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