期刊：
IEEE INTERNET OF THINGS JOURNAL,2020年7(10):9919-9929 ISSN：2327-4662
通讯作者：
Yi, Lingzhi
作者机构：
[Deng, Xianjun; Jiang, Yalan] Univ South China, Sch Elect Engn, Hunan Prov Key Lab Ultrafast Micro Nano Technol &, Hengyang 421001, Peoples R China.;[Yang, Laurence T.; Yi, Lingzhi] St Francis Xavier Univ, Dept Comp Sci, Antigonish, NS B2G 2W5, Canada.;[Yi, Lingzhi] Univ South China, Sch Civil Engn, Hengyang 421001, Peoples R China.;[Chen, Jiaoyan] Nanchang Univ, Sch Informat Engn, Nanchang 330031, Jiangxi, Peoples R China.;[Liu, Yong; Li, Xiangyang] Univ South China, Sch Resource Environm & Safety Engn, Hunan Prov Engn Res Ctr Radioact Control Technol, Hengyang 421001, Peoples R China.
通讯机构：
[Yi, Lingzhi] U;Univ South China, Sch Civil Engn, Hengyang 421001, Peoples R China.
关键词：
Oceans;Learning automata;Surveillance;Sensors;Internet of Things;Peer-to-peer computing;Barrier coverage;confident information coverage (CIC) model;Internet of Things (IoT);learning automata (LA);smart ocean
摘要：
As an emerging network paradigm, the Internet of Things (IoT) which consists of a significant number of multifunctional and heterogeneous IoT nodes has attracted dramatic attentions from both academia and industry. With the merits of intelligent capacity, desirable scalability, and high reliability, the IoT recently has been applied for smart ocean applications to provide protection for ocean environment monitoring and surveillance. Aiming to provide coverage service for ocean border environmental surveillance, this article studies the barrier coverage problem which investigates how to select a collection of IoT nodes to obtain an IoT node chain and build barrier paths to detect intruders and trespassers crossing the border region of interest. To overcome the disadvantages in the existing works on barrier coverage, we adopt a novel and widely adopted confident information coverage (CIC) model as the fundamental coverage model and formulate the CIC barrier path construction (CICBC) problem with the goals of maximizing the number of barrier paths and minimizing the amount of IoT nodes in each barrier path. We propose a distributed CIC barrier path (CICBP) construction approach based on learning automata (CBLA). The CBLA includes four crucial phases which are initialization phase, learning phase, monitoring phase, and repairing phase. Each IoT node equips a learning automaton. CBLA selects an optimal IoT node to construct the barrier path by learning. The simulation results show that the performance of the CBLA algorithm outperforms two peer algorithms in terms of the number of barrier paths and the average number of nodes in each barrier path.
摘要：
It is the fact that there are lots of hazard incidents in underground uranium mines caused by radon but in-suit uranium samples were difficult to collect. Based on closed chamber method, three similar samples in different sealed ways were made in a laboratory with different material rations, namely uranium tailings, quartz sand, cement, iron powder and silicon powder to measure the radon concentrations with and without low-frequency vibrations, which was used by the experimental device for low-frequency vibration diffusion of radon. The results showed that the radon exhalation coming from the similar samples was influenced by the low frequency vibration; the results are presented as two-stage variations compared with the blank group. The radon exhalation increased with the rising vibration frequency when the frequency was 50 to 70 Hz, but fell slowly after reaching the peak radon exhalation rate. Analyses of the relations between the rock damage degree, changes in porosity and the occurrence of an inflection point in the radon exhalation rate in the samples found that they also increased when the frequency was between 0 to 80 in sample 3. The maximum porosity of the third samples was about 4.8% with a low-frequency vibration 60 Hz, while the maximum damage degree was about 0.07 at 50 Hz.
