无人机辅助传感数据聚合:增量聚类和调度方法

Tien-Dung Nguyen, D. Le, Nguyen Pham-Van, Hyunseung Choo, T. P. Van
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引用次数: 3

摘要

使用无人驾驶飞行器(uav)已被认为是一种有效的方式来收集数据从传感器网络跨越广泛的区域。现有方案通常将网络划分为若干个簇,由无人机逐个访问簇头,收集收集到的数据。然而,他们只解决了如何有效地规划无人机的轨迹,而忽略了每个集群内的数据聚合时间。提出了一种增量聚类调度方案,根据无人机的飞行轨迹和飞行速度计算传感器的传输调度。无人机稍后访问的簇头将被给予更多的时间从其簇收集数据。因此,数据聚合时间明显缩短。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
UAV-aided Sensory Data Aggregation: Incremental Clustering and Scheduling Approach
Using unmanned aerial vehicles (UAVs) has been considered as an effective way to collect data from a sensor network spanning over a wide area. Existing schemes usually divide the network into several clusters, and the UAV visits the cluster heads one by one to collect the gathered data. However, they only solved how to efficiently plan the UAV trajectory and neglected the data aggregation time within each cluster. This paper proposes an incremental clustering and scheduling scheme, in which the transmission schedule of sensors is calculated in line with the UAV trajectory and velocity. The cluster head that the UAV visits at a later time will be given more time to collect data from its cluster. As a result, the data aggregation time is significantly shorter.
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