计算机科学
文件传输协议
无线传感器网络
弹道
灵活性(工程)
基站
路径(计算)
最优化问题
实时计算
分布式计算
数学优化
计算机网络
算法
数学
物理
万维网
互联网
统计
天文
作者
Chuanwen Luo,Meghana N. Satpute,Deying Li,Yongcai Wang,Wenping Chen,Weili Wu
出处
期刊:IEEE ACM Transactions on Networking
[Institute of Electrical and Electronics Engineers]
日期:2020-01-01
卷期号:: 1-14
被引量:10
标识
DOI:10.1109/tnet.2020.3027555
摘要
The increasing availability of autonomous small-size Unmanned Aerial Vehicles (UAVs) has provided a promising way for data gathering from Wireless Sensor Networks (WSNs) with the advantages of high mobility, flexibility, and good speed. However, few works considered the situations that multiple UAVs are collaboratively used and the fine-grained trajectory plans of multiple UAVs are devised for collecting data from network including detailed traveling and hovering plans of them in the continuous space. In this paper, we investigate the problem of the Fine-grained Trajectory Plan for multi-UAVs (FTP), in which m UAVs are used to collect data from a given WSN, where m ≥ 1. The problem entails not only to find the flight paths of multiple UAVs but also to design the detailed hovering and traveling plans on their paths for efficient data gathering from WSN. The objective of the problem is to minimize the maximum flight time of UAVs such that all sensory data of WSN is collected by the UAVs and transported to the base station. We first propose a mathematical model of the FTP problem and prove that the problem is NP-hard. To solve the FTP problem, we first study a special case of the FTP problem when m = 1, called FTP with Single UAV (FTPS) problem. Then we propose a constant-factor approximation algorithm for the FTPS problem. Based on the FTPS problem, an approximation algorithm for the general version of the FTP problem when m > 1 is further proposed, which can guarantee a constant factor of the optimal solution. Afterwards, the proposed algorithms are verified by extensive simulations.
科研通智能强力驱动
Strongly Powered by AbleSci AI