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Virtual Forces based UAV Fleet Mobility Models for Air Pollution Monitoring

机译:基于虚拟部队的无人机机队机动模型用于空气污染监测

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One of the main issues in UAVs networks design is how nodes are relocated in order to meet the desired performance objectives. In this work, we propose two UAVs fleet mobility models based on the Virtual Forces Algorithm (VFA). The application context we are interested in is the air pollution surveillance over wide areas. The first model is a centralized variant where all computations are performed in a central ground base station. While the second model is a distributed version where each node takes its own decision in collaboration with its neighbors. We evaluate our models performances and we compare them with state of the art solutions using a real data set of air pollution concentrations and according to three main metrics: the maximal estimation error, execution time and communication cost.
机译:UAV网络设计中的主要问题之一是如何重定位节点以满足所需的性能目标。在这项工作中,我们提出了两个基于虚拟力算法(VFA)的无人机机队机动性模型。我们感兴趣的应用环境是大范围的空气污染监测。第一个模型是集中式变体,其中所有计算都在中央地面基站中执行。第二种模型是分布式版本,其中每个节点都与其邻居协作做出自己的决定。我们评估模型的性能,并使用真实的空气污染浓度数据集并根据三个主要指标将它们与最新解决方案进行比较:最大估计误差,执行时间和通信成本。

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