基于区域划分聚类的无人机网络数据采集算法

Khedidja Medani, Houssem Guemer, Z. Aliouat, S. Harous
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引用次数: 4

摘要

在本文中,我们将无人机视为具有飞行能力的移动传感器,在大范围的监督区域内提供及时和准确的视觉。为了将收集到的数据路由到地面上的控制站,这些无人机的互连构成了飞行自组网(FANET)。然而,无人机的特点给数据收集和路由带来了挑战性问题。因此,由于无人机的高机动性,通信容易出现高频链路断开。在本文中,我们提出了一个可靠的架构来收集和路由数据到地面站(GS)。提出的基于简单区域划分聚类的算法(SAD-CA)通过聚类技术提供稳定的网络结构,以应对无人机的高机动性,同时保持无人机的能量消耗。利用网络模拟器3 (NS3)对所提出的算法进行了性能评估,在能耗和网络寿命方面显示出令人信服的结果,优于参考协议所展示的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Area Division Cluster-based Algorithm for Data Collection over UAV Networks
In this paper, we consider the unmanned aerial vehicles (UAVs) as mobile sensors with flying ability to provide a timely and accurate vision over a large supervised area. The interconnection of these UAVs, in order to route the collected data to the control station on the ground, constitutes the flying ad hoc network (FANET). However, the UAVs features impose challenging issues to data collection and routing. Thus, the communications are prone to high-frequency link disconnections caused by the high mobility of UAVs. In this paper, we propose a reliable architecture to collect and route data to a ground station (GS). The proposed simple area division cluster-based algorithm (SAD-CA) provides a stable network architecture through the clustering technique in order to deal with the high mobility of the UAVs while preserving their energy consumption. The performance evaluation of the proposed algorithm, carried out using the network simulator 3 (NS3), has shown convincing results, in terms of energy consumption and network lifetime, outperforming those exhibited by the referred protocol.
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