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Abstract
The key to the study of node deployment in Wireless Sensor Networks (WSN) is to find the appropriate location of the WSN nodes and reduce the cost of network deployment while meeting the monitoring requirements in the covered area. This paper proposes a WSN node deployment algorithm based on real 3D terrain, which provides an effective solution to the surface-covering problem. First of all, actual geographic elevation data is adopted to conduct surface modeling. The model can vividly reflect the real terrain characteristics of the area to be deployed and make the deployment plan more visible and easy to adjust. Secondly, a probabilistic coverage model based on DEM (Digital Elevation Model) data is proposed. Based on the traditional spherical coverage model, the influence of signal attenuation and terrain occlusion on the coverage model is added to make the deployment model closer to reality. Finally, the Greedy algorithm based on grid scanning is used to deploy nodes. Simulation results show that the proposed algorithm can effectively improve the coverage rate, reduce the deployment cost, and reduce the time and space complexity in solving the WSN node deployment problem under the complex 3D land surface model, which verifies the effectiveness of the proposed algorithm.
Highlights
Wireless Sensor Networks (WSNs) are composed of wireless sensor network nodes, which transmit the information collected in the detection area to the sink node in a selforganizing and multi-hop way, thereby actualizing the monitoring of the information in the detection area
Based on the above ideas, this paper proposes a WSN node deployment algorithm based on real three-dimensional terrain, which uses the real terrain elevation data downloaded from a network geographic database to reconstruct and model the surface
Combining the above two models, the WSN proba model based on Digital Elevation Model (DEM) data is obtained as: This model comprehensively considers the influence of the terrain shading and signal attenuation on the node coverage model, so the model can more genuinely reflect the perceived effect of the node in the actual environment
Summary
Wireless Sensor Networks (WSNs) are composed of wireless sensor network nodes, which transmit the information collected in the detection area to the sink node in a selforganizing and multi-hop way, thereby actualizing the monitoring of the information in the detection area. The current states and progress of the 3D surface-covering problem are outlined: Boufares [18] proposes a distributed deployment algorithm (3D-IDVFA-TC) based on the improved virtual force strategy, which can effectively improve the coverage rate of different complex Z-degree surface function models while ensuring network connectivity and reducing node loss. The above algorithms can achieve a better deployment effect in the WSN surface-coverage problem, four significant issues have yet to be addressed: first of all, the model of the area to be deployed still uses the simple surface generated by the function, which is too regular and smooth to simulate the surface characteristics of the real terrain environment. To solve the WSN deployment problem of real three-dimensional terrain more effectively, a deployment algorithm that can fully integrate terrain data and node coverage model characteristics is required. The Greedy algorithm based on grid scanning is employed to solve the WSN node problem, which significantly reduced the time and space complexity of
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