An Integral Data Gathering Framework for Supervisory Control and Data Acquisition Systems in Green IoT

被引:11
作者
Xiang, Xuemei [1 ]
Gui, Jinsong [1 ]
Xiong, Neal N. [1 ,2 ]
机构
[1] Cent South Univ, Sch Comp Sci & Engn, Changsha 410083, Peoples R China
[2] Northeastern State Univ, Dept Math & Comp Sci, Tahlequah, OK 74464 USA
来源
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING | 2021年 / 5卷 / 02期
基金
中国国家自然科学基金;
关键词
Data collection; Sensors; SCADA systems; Wireless sensor networks; Energy consumption; Internet; Unmanned aerial vehicles; Green Internet of Things; SCADA system; energy saving; data collection; unmanned aerial vehicles; BIG DATA; NETWORKS; AWARE; INTERNET; SCHEME; THINGS;
D O I
10.1109/TGCN.2021.3068257
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
In Green Internet of Things, energy consumption research is a hot topic. Our research focuses on Supervisory Control And Data Acquisition (SCADA) system, and it is a system consisting of a plurality of self-organized sensing networks. Live data gathering from numerous Sub-connected SCADA (S-SCADA) networks to make unified decisions based on collected data is one of pivot problem, which has not been well studied. In this article, an integral data-gathering framework is proposed to prolong network lifetime by using sink rotating and Unmanned Aerial Vehicles (UAV) path planning. In the proposed Sink Rotating joint UAV Data Gathering (SR-UAV-DG) framework, the data gathering process is divided into two organic components: (a) S-SCADA in-network data collection. The energy consumption of the network is balanced by selecting the node with the least energy consumption as the sink node. (b) Use UAV for data collection between S-SCADA networks. The theoretical analysis results show that the SR-UAV-DG framework proposed in this article reduces the maximum energy consumption of nodes in the network by 99.21% after 1000 rounds of data. The flight time of UAV is reduced by 16.83%. In the case of unreliable communication links, the data reception rate is guaranteed to reach 91.94%.
引用
收藏
页码:714 / 726
页数:13
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