In unmanned aerial vehicle (UAV)-aided wireless sensor networks (UWSNs), a UAV is employed as a mobile sink to gather data from sensor nodes. Incorporating UAV helps prolong the network lifetime and avoid the energy-hole problem faced by sensor networks. In emergency applications, timely data collection from sensor nodes and transferal of the data to the base station (BS) is a prime requisite. The timely and safe path of UAV is one of the fundamental premises for effective UWSN operations. It is essential and challenging to identify a suitable path in an environment comprising various obstacles and to ensure that the path can efficiently reach the target point. This paper proposes a hybrid path planning (HPP) algorithm for efficient data collection by assuring the shortest collision-free path for UAV in emergency environments. In the proposed HPP scheme, the probabilistic roadmap (PRM) algorithm is used to design the shortest trajectory map and the optimized artificial bee colony (ABC) algorithm to improve different path constraints in a three-dimensional environment. Our simulation results show that the proposed HPP outperforms the PRM and conventional ABC schemes significantly in terms of flight time, energy consumption, convergence time, and flight path.
Unmanned aerial vehicle (UAV)-aided wireless sensor networks (UWSNs) can be effectively used for time-critical sensing applications. UAVs can be used to collect the sensed data from sensors and transfer them to a base station. The real-time transfer of data is highly desired in the time-critical applications. However, the medium access control (MAC) protocols designed for UWSNs so far are primarily focused on the efficient use of UAVs to collect data in the sensing areas. In this paper, we propose an energy-efficient and fast MAC (EF-MAC) protocol in UWSNs for time-critical sensing applications. EF-MAC adopts carrier sense multiple access (CSMA) for the registration of sensor nodes with a UAV and time division multiple access (TDMA) with variable slot time for the transmission of collected data. The UAV is equipped with two transceivers to minimize both energy consumption and delay in air-to-ground communication. The energy consumption and delay are formally analyzed and the performance of EF-MAC is evaluated via extensive simulation. The simulation results show that the proposed EF-MAC outperforms the conventional MAC protocols in terms of energy efficiency and communication delay.
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