UAV-Assisted Data Collection for Ocean Monitoring Networks

被引:34
作者
Ma, Ruofei [1 ]
Wang, Ruisong [2 ]
Liu, Gongliang [2 ]
Chen, Hsiao-Hwa [3 ]
Qin, Zhiliang [4 ]
机构
[1] Harbin Inst Technol, Dept Commun Engn, Weihai, Peoples R China
[2] Harbin Inst Technol, Weihai, Peoples R China
[3] Natl Cheng Kung Univ, Dept Engn Sci, Tainan, Taiwan
[4] Weihai Beiyang Elect Grp Co Ltd, Weihai, Shandong, Peoples R China
来源
IEEE NETWORK | 2020年 / 34卷 / 06期
基金
中国国家自然科学基金;
关键词
Data acquisition - Vehicle to vehicle communications - Convex optimization - Surface waters - Energy efficiency - Integer programming - Underwater acoustics - Antennas - Underwater acoustic communication;
D O I
10.1109/MNET.011.2000168
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Ocean monitoring network (OMN) is a remote oceanic data collection system, which integrates communication and networking technologies. As underwater acoustic communication has been widely used for data transmission between battery- powered underwater sensor nodes (USNs) and sink nodes (SNs), an oceanic data collection system requires energy efficient deployment to prolong the lifetime of the whole network. This work aims to propose an unmanned aerial vehicle (UAV) assisted OMN architecture, in which sensing data are transmitted first from USNs to sea surface SNs in each data collection cycle using underwater acoustic communication, and then a UAV hovering above the SNs collects and relays all the data to a ground base station via wireless communication links. To extend the network lifetime, we model SNs and UAV deployment and resource allocation as a mixed integer non-convex optimization problem. To solve the problem efficiently in a heuristic way, we design a SNs deployment scheme with the help of time division USN-to-SN access and NOMA based SN-to-UAV access schemes. Computer simulations validate the superiority of the proposed deployment and access schemes on OMN lifetime performance. in particular, increasing the number of time slots in the USN-to-SN access process can improve the performance significantly.
引用
收藏
页码:250 / 258
页数:9
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