A Novel UAV-Enabled Data Collection Scheme for Intelligent Transportation System Through UAV Speed Control

数据收集 计算机科学 实时计算 节点(物理) 方案(数学) 控制(管理) 数据挖掘 模拟 工程类 人工智能 数学分析 统计 数学 结构工程
作者
Xiong Li,Jiawei Tan,Anfeng Liu,Pandi Vijayakumar,Neeraj Kumar,Mamoun Alazab
出处
期刊:IEEE Transactions on Intelligent Transportation Systems [Institute of Electrical and Electronics Engineers]
卷期号:22 (4): 2100-2110 被引量:127
标识
DOI:10.1109/tits.2020.3040557
摘要

The rapid and convenient travel of people and the timely transportation of goods depend on the correct decision of the Intelligent Transportation Systems (ITS). Due to the decision-making of ITS requires a large amount of data to support, UAV-enabled periodic data collection is an effective method. However, due to the limited resources of UAV, UAV cannot directly collect data from all storage devices, resulting in unfair data collection. Therefore, we propose a UAV Speed Control based Fairness Data Collection (USCFDC) scheme. First, since the fairness of data collection will affect the decision-making of ITS, a framework for controlling the flight speed of the UAV is proposed to improve the fairness of data collection. The flight speed of UAV will slow down in areas with a large number of nodes, thereby improving the fairness of data collection. Second, a novel method is proposed to maximize the amount of data collected by UAV from each node. With this method, the value of the amount of data will be used as the dichotomous value in the dichotomy algorithm, and the UAV must collect a certain amount of data from each node. The upper and lower limits of the dichotomy algorithm are adjusted according to the time duration for UAV to collect data. Compared with previous schemes, the fairness of data collection can be improved by a maximum of 15.89% under the same flight time of UAV. Besides, the energy consumption is reduced by 49.31%-52.55% and the flight time of the UAV is reduced by 48%-62.38% when the amount of collected data is the same.

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