2018 · 33 citations · 30 references
ComputingComputer SystemsAerial RoboticsCluster ComputingUnmanned Aircraft SystemsDistributed Sensor NetworksSensor NetworksWireless Sensor NetworksEnergy-efficient Data TransmissionEnergy-efficient ProtocolsEnergy-efficient Wireless Sensor NetworksGenetic Algorithm OptimizationNetwork LifetimeNetwork Lifetime OptimizationNetwork Performance OptimizationWireless Sensor Network Protocols
Energy efficiency is an important issue in Wireless Sensor Networks (WSNs). The energy is mainly consumed by data sensing, data transmission and movement of sensors. The energy consumed by data transmission is much larger than data sensing. A potential solution for energy saving is applying the external devices to collect data to prolong the network lifetime. In this paper, we adopt an unmanned aerial vehicle (UAV) serving as the data mule and propose a novel energy-efficient UAV-based data aggregation protocol in WSNs to reduce the energy consumption of sensors. By considering a clustered WSN, our approach computes an optimal path for data mule through all cluster heads (CHs) while achieving a relatively high system-wide energy efficiency. Moreover, we introduce a genetic algorithm to derive a near-optimal solution for a large-scale WSN while reducing the computing time. We compare our protocol with state-of-the-art approaches, and the simulation results demonstrate that the proposed algorithm improves the network performance on energy efficiency.
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