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协作式无人机-无线传感器网络分布式应用的时间约束节点访问规划

Time-Constrained Node Visit Planning for Collaborative UAV-WSN Distributed Applications.

作者信息

Augello Andrea, Gaglio Salvatore, Lo Re Giuseppe, Peri Daniele

机构信息

Department of Engineering, University of Palermo, Viale delle Scienze, Ed. 6, 90128 Palermo, Italy.

Institute for High Performance Computing and Networking (ICAR), National Research Council (CNR), Via Ugo La Malfa, 153, 90146 Palermo, Italy.

出版信息

Sensors (Basel). 2022 Jul 15;22(14):5298. doi: 10.3390/s22145298.

Abstract

Unmanned Aerial Vehicles (UAVs) are often studied as tools to perform data collection from Wireless Sensor Networks (WSNs). Path planning is a fundamental aspect of this endeavor. Works in the current literature assume that data are always ready to be retrieved when the UAV passes. This operational model is quite rigid and does not allow for the integration of the UAV as a computational object playing an active role in the network. In fact, the UAV could begin the computation on a first visit and retrieve the data later. Potentially, the UAV could orchestrate the distributed computation to improve its performance, change its parameters, and even upload new applications to the sensor network. In this paper, we analyze a scenario where a UAV plays an active role in the operation of multiple sensor networks by visiting different node clusters to initiate distributed computation and collect the final outcomes. The experimental results validate the effectiveness of the proposed method in optimizing total flight time, Average Age of Information, Average cluster computation end time, and Average data collection time compared to prevalent approaches to UAV path-planning that are adapted to the purpose.

摘要

无人驾驶飞行器(UAV)常被作为从无线传感器网络(WSN)进行数据收集的工具来研究。路径规划是这项工作的一个基本方面。当前文献中的研究工作假设,当无人机经过时数据总是随时可供检索。这种操作模式相当僵化,不允许将无人机作为在网络中发挥积极作用的计算对象进行整合。事实上,无人机可以在首次访问时就开始计算,之后再检索数据。潜在地,无人机可以协调分布式计算以提高其性能、更改其参数,甚至向传感器网络上传新应用。在本文中,我们分析了一种场景,即无人机通过访问不同的节点集群来启动分布式计算并收集最终结果,从而在多个传感器网络的运行中发挥积极作用。实验结果验证了与适用于该目的的普遍无人机路径规划方法相比,所提方法在优化总飞行时间、平均信息年龄、平均集群计算结束时间和平均数据收集时间方面的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2b3/9315616/eda3529c313a/sensors-22-05298-g001.jpg

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