Abstract
AbstractUnmanned aerial vehicles (UAVs) provide an energy-efficient and robust solution for data collection from the internet of things (IoT) devices. However, the UAV’s deployment optimization, including locations of the UAV’s stop points, is necessary to save the overall energy consumption and conduct the data collection efficiently. Thus, the objective is to minimize the energy consumption of the UAV and the IoT devices while collecting the data efficiently. This chapter proposes gaining-sharing knowledge (GSK) algorithm for optimizing the UAV’s deployment. In GSK, the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed-length representing an entire deployment. The validity of using GSK is verified by simulation in five IoT device distribution scenarios. It provides significant results in all five scenarios compared to the other three optimization algorithms.KeywordsGSKIoTUAVStop pointsOptimization
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