| Citation: |
WANG Ke, GUAN Huizhen, ZHANG Lili, CHAO Yi, ZHANG Yuanben, DING Xuan , HU Chuli. Sensor Coverage Deployment Method in Continuous Three‑Dimensional Space： A Case Study of Water Quality Monitoring[J]. Geomatics and Information Science of Wuhan University, 2024, 49(2): 271-279. DOI: 10.13203/j.whugis20210325
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Coverage and communication are of great significance to the accuracy, comprehensiveness and data transmission of sensor network monitoring, especially in the case of different vertical monitoring requirements, traditional monitoring methods are difficult to achieve good coverage effect. We proposed a node coverage deployment method based on 3D finite dominating sets to solve the above problem.
The node deployment problem in continuous space is transformed into discrete maximum coverage location problem by 3D finite dominating sets. First, the continuous space is discretized by cubes, each cube is weighted according to the actual monitoring needs. A set of 3D finite dominating sets which can represent the infinite candidate positions in the continuous space is extracted. Then, a maximum coverage model considering communication is constructed to get the optimal deployment location of the sensors. Take water quality testing as an example, the underwater sensors deployment simulation is carried out. The communication effect between sensors and the influence of discrete size on the result are analyzed, and the coverage of this method compared with other methods was elucidated.
The results show that, the sensor deployment method proposed in this study can effectively improve the coverage in the continuous three-dimensional space, achieve higher coverage through fewer nodes, and ensure the communication between sensors even if there are few deployed sensors. In addition, when the discretization size is small, the solution time is long, and the error between the model coverage and the actual coverage is small. On the contrary, when the discretization scale is large, the solving efficiency is high, but the error is relatively large.
The proposed method can effectively solve the problem of sensor deployment in three-dimensional space and efficiently obtain the data related to the monitored elements with different spatial distribution in vertical direction.
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