[1] Yan Feng, Chen Jiahui, Wu Tao, Li Hao, et al. UAV trajectory planning algorithmfor data collection in wireless sensor networks [J]. Journal of Southeast University (English Edition), 2020, 36 (4): 376-384. [doi:10.3969/j.issn.1003-7985.2020.04.002]

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UAV trajectory planning algorithmfor data collection in wireless sensor networks()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

36

Issue:

2020 4

Page:

376-384

Research Field:

Information and Communication Engineering

Publishing date:

2020-12-20

Info

Title:

UAV trajectory planning algorithmfor data collection in wireless sensor networks

Author(s):

Yan Feng¹;  Chen Jiahui¹;  Wu Tao²;  Li Hao³;  Pang Jingming²Liu Wanzhu²;  Xia Weiwei¹;  Shen Lianfeng¹

¹National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
²Jiangsu Zhongli Electronic Information Sci-Tech Co., Ltd., Changshu 215542, China
³Science and Technology on Near-Surface Detection Laboratory, Wuxi 214035, China

Keywords:

unmanned aerial vehicle;  wireless sensor networks;  trajectory planning;  data collection;  value of information

PACS:

TN929.5

DOI:

10.3969/j.issn.1003-7985.2020.04.002

Abstract:

In order to maximize the value of information(VoI)of collected data in unmanned aerial vehicle(UAV)-aided wireless sensor networks(WSNs), a UAV trajectory planning algorithm named maximum VoI first and successive convex approximation(MVF-SCA)is proposed. First, the Rician channel model is adopted in the system and sensor nodes(SNs)are divided into key nodes and common nodes. Secondly, the data collection problem is formulated as a mixed integer non-linear program(MINLP)problem. The problem is divided into two sub-problems according to the different types of SNs to seek a sub-optimal solution with a low complexity. Finally, the MVF-SCA algorithm for UAV trajectory planning is proposed, which can not only be used for daily data collection in the target area, but also collect time-sensitive abnormal data in time when the exception occurs. Simulation results show that, compared with the existing classic traveling salesman problem(TSP)algorithm and greedy path planning algorithm, the VoI collected by the proposed algorithm can be improved by about 15% to 30%.

References:

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Memo

Memo:

Biography: Yan Feng(1983—), male, doctor, associate professor, feng.yan@seu.edu.cn.
Foundation items: The National Key R& D Program of China(No.2018YFB1500800), the Specialized Development Foundation for the Achievement Transformation of Jiangsu Province(No.BA2019025), Pre-Research Fund of Science and Technology on Near-Surface Detection Laboratory(No.6142414190405), the Open Project of the Key Laboratory of Wireless Sensor Network & Communication of Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences(No.20190907).
Citation: Yan Feng, Chen Jiahui, Wu Tao, et al. UAV trajectory planning algorithm for data collection in wireless sensor networks[J].Journal of Southeast University(English Edition), 2020, 36(4):376-384.DOI:10.3969/j.issn.1003-7985.2020.04.002.

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