无线视频传感器网络全视角弱栅栏构建算法

郭新明; 林德钰; 陈伟

doi:10.13433/j.cnki.1003-8728.20230038

无线视频传感器网络全视角弱栅栏构建算法

doi: 10.13433/j.cnki.1003-8728.20230038

1.
咸阳师范学院计算机学院，陕西咸阳　712000
2.
南昌大学软件学院，南昌　330027

基金项目: 国家自然科学基金面上项目（61762061）、陕西省重点研发计划项目（2020NY-175）、陕西省教育厅服务地方项目（19JC041）、江西省自然科学基金项目（20224BAB212016）及咸阳师范学院 “ 学术带头人”（XSYXSDT202124）

详细信息

作者简介:
郭新明（1979−），副教授，硕士生导师，研究方向为物联网技术，guoxinming118@126.com

中图分类号: TP393
计量
- 文章访问数: 142
- HTML全文浏览量: 59
- PDF下载量: 17
- 被引次数: 0
出版历程
- 收稿日期: 2022-05-11
- 网络出版日期: 2023-03-27
- 刊出日期: 2023-02-25

Full-view Weak Barrier Coverage Construction Algorithm forWireless Visual Sensor Networks

1.
School of Computer, Xianyang Normal University, Xianyang 712000, Shaanxi, China
2.
School of Software, Nanchang University, Nanchang 330027 , China

摘要

摘要: 针对利用无线视频传感器网络（WVSN）全视角弱栅栏进行入侵行为检测的问题，建立了一种WVSN全视角弱栅栏覆盖几何模型，采用网格化方法将其离散化，把WVSN最优全视角弱栅栏覆盖问题表示成整数规划形式，并证明其是NP-hard的，进而提出了一个网格厚度优先的WVSN弱栅栏覆盖的启发式算法GTPFWBC。为验证该算法的有效性，进行了大量仿真实验。实验结果显示GTPFWBC算法能较好地解决WVSN的全视角弱栅栏覆盖问题，其全视角栅栏构造成功率明显优于W-GraProj、SP和DP1算法，且生成WVSN栅栏的平均节点数分别比W-GraProj和SP大约节省30.6%和59.4%，另外GTPFWBC的时间复杂度远小于W-GraProj、SP和DP1，因此在能量受限、实时性要求较高的WVSN中GTPFWBC算法的效果更佳。
- 无线视频传感器网络 /
- 全视角 /
- 弱栅栏 /
- 启发式算法
Abstract: A full-view weak barrier coverage geometric model was proposed in this paper, with the aim of solving the problem of intrusion detection based on full-view weak barrier coverage in wireless visual sensor networks (WVSN), and the full-view weak barrier coverage problem can be discretized through the grid method. Besides, the problem can be expressed as an integer programming problem which is proven being a NP-Hard. Subsequently, a heuristic algorithm of grid thickness priority WVSN full-view weak barrier coverage (GTPFWBC) was proposed. To verify the effectiveness of the algorithm, extensive simulation experiments were conducted already. The experimental results shown that GTPFWBC is able to solve the full-view weak barrier coverage problem of WVSN effectively. The success rate of GTPFWBC in constructing full-view barriers is obviously better than W-Graproj, SP and DP1 algorithms. Compared with W-Graproj and SP, the average number of nodes for constructing WVSN barriers is about 30.6% and 59.4% less, respectively. In addition, the time complexity of GTPFWBC is much smaller than that of W-GraProj, SP and DP1. Therefore, the conclusion that the effectiveness of GTPFWBC algorithm is much better in WVSN with limited energy and high real-time requirements can be drawn.
- wireless visual sensor networks /
- full-view /
- weak barriers /
- heuristic algorithm

HTML全文

图 1 无线视频传感器感知模型示意图

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图 2 视频传感器全视角覆盖示意图

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图 3 监测目标朝向的取值范围示意图

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图 4 视频传感器有效捕获区示意图

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图 5 穿越路径上多传感器有效朝向集整合图

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图 6 视频传感器的最大收缩区

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图 7 WVSN全视角弱栅栏覆盖模型

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图 8 WVSN覆盖区域网格划分图

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图 9 完整覆盖网格示意图

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图 10 网格厚度示意图

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图 11 GTPFWBC算法流程图

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图 12 全视角栅栏构建成功率与部署节点数量的关系

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图 13 栅栏构建平均节点数与传感器部署数量的关系

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