起伏地形下无线传感器网络节点部署算法

吕安琪; 李翠然; 谢健骊; 刘莉

doi:10.3969/j.issn.0258-2724.20230715

起伏地形下无线传感器网络节点部署算法

doi: 10.3969/j.issn.0258-2724.20230715

兰州交通大学电子与信息工程学院，甘肃兰州 730070

基金项目: 国家自然科学基金资助项目（62161016）

详细信息

作者简介:
吕安琪（1994—），女，博士研究生，研究方向为无线传感器网络，E-mail：18093194674@163.com

通讯作者:
李翠然（1975—），女，教授，博士，研究方向为高铁智能无线通信、无线传感器网络和协同通信技术，E-mail：licr@mail.lzjtu.cn

中图分类号: TP391
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- 文章访问数: 62
- HTML全文浏览量: 29
- PDF下载量: 7
- 被引次数: 0
出版历程
- 收稿日期: 2023-12-29
- 修回日期: 2024-05-15
- 网络出版日期: 2025-04-09

Node Deployment Algorithm for Wireless Sensor Network in Rolling Terrain

School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China

摘要

摘要:
为减少起伏地形下传感器节点的部署数量，首先，采用数字高程模型与Delaunay三角剖分对起伏地形表面建模，确定节点部署问题解空间；然后，建立节点部署算法搜索维度与网络覆盖率之间的函数关系，以网络连通为约束、网络覆盖率最大化为目标，并基于改进海洋捕食者算法，搜索形成候选个体集；再以收益遗憾最小化为准则，使用候选个体衍生新个体；最后，将网络覆盖率、网络密度作为指标构建筛选函数，选出最佳新个体并纳入到部署节点集合. 仿真结果表明：在地形粗糙度为1.9、目标覆盖率为80%～100%时，与同类部署算法相比，所提算法的节点部署数量降低2.9%～69.1%；在地形粗糙度为1.3～2.5、目标覆盖率为100%时，所提算法的节点部署数量降低3.1%～74.0%，网络生命周期有所延长.
- 无线传感器网络 /
- 节点部署 /
- 地形粗糙度 /
- 网络生命周期
Abstract:
To reduce the number of sensor nodes deployed in rolling terrains, firstly, the digital elevation model and Delaunay triangulation were used to model the rolling terrain surface and determine the solution space of the node deployment problem. Secondly, the functional relationship between the node deployment algorithm search dimension and network coverage rate was established. A candidate individual set was searched and formed based on the proposed improved marine predator algorithm, with the constraints of network connectivity and the goal of maximizing network coverage rate. The utility regret minimization criterion was used to derive new individuals from the candidate individuals. Finally, the filtering function was constructed using network coverage rate and network density as indicators to select the best new individual and incorporate it into the deployed node set. Simulation results show that compared with similar deployment algorithms, the proposed algorithm reduces the number of deployed nodes by 2.9%–69.1% for terrain roughness at 1.9 and target coverage rate at 80%–100% and that by 3.1%–74.0% for the terrain roughness at 1.3–2.5 and the target coverage rate at 100%, and the network lifetime is prolonged.
- wireless sensor network /
- node deployment /
- terrain roughness /
- network lifetime

HTML全文

图 1 起伏地形表面模型

Figure 1. Model of rolling terrain surface

下载: 全尺寸图片幻灯片

图 2 通视模型

Figure 2. Line of sight model

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图 3 地形示意

Figure 3. Schematic diagram of terrains

下载: 全尺寸图片幻灯片

图 4 算法性能随$ \eta _{\text{t}} $变化趋势

Figure 4. Variation of algorithm performance with $ \eta _{\text{t}} $

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图 5 算法性能随τ变化趋势

Figure 5. Variation of algorithm performance with τ

下载: 全尺寸图片幻灯片

表 1 仿真参数及取值

Table 1. Simulation parameters and values

参数	取值
起伏地形：长/宽/高 m	100/100/50
DEM网格精度	21 × 21
IMPA种群大小	50
权重$ \theta _0 $	0.9
节点初始能量/J	1
数据包大小/bit	3200
电路能耗$ E_{\text{elec}} $/（nJ•bit⁻¹）	50
功放参数$ \varepsilon _{\text{fs}} $/（ pJ•bit⁻¹•m⁻²）	10
功放参数$ \varepsilon _{\text{amp}} $/（pJ•bit⁻¹•m⁻⁴）	0.0013
距离阈值$ d_0 $/m	87

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