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一个混合定位框架用于大规模的三维物联网环境.

Shima Koulaeizadeh1, Hatef Javadi2, Sudabeh Gholizadeh3

  • 1Communication Networks, Technische Universität, 09111 Chemnitz, Germany.

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概括
此摘要是机器生成的。

本研究介绍了一种新的无GPS定位框架,用于3D物联网 (IoT) 和边缘计算 (EC) 环境. 拟议的方法通过整合DV-Hop,JS和ARO算法来提高数据的准确性,比现有解决方案高出39%的精度.

关键词:
距离向量-跳跃在本地化,本地化.优化的优化优化优化.定位定位 定位定位这是一个三维的物联网.

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科学领域:

  • 计算机科学 计算机科学
  • 电气工程 电气工程
  • 网络工程 网络工程

背景情况:

  • 物联网 (IoT) 和边缘计算 (EC) 对现代应用至关重要,但需要准确的数据源本地化.
  • 全球定位系统 (GPS) 由于覆盖范围,能源和干扰问题,通常不适合物联网/EC.
  • 准确的地理来源确定对于物联网和EC中感知数据的意义至关重要.

研究的目的:

  • 为三维 (3D) 边缘计算 (EC) 环境提出一个创新的无GPS定位框架.
  • 在物联网和EC场景中解决GPS的局限性.
  • 提高3D物联网/EC系统中数据源定位的准确性和效率.

主要方法:

  • 对3D环境的距离向量跳转 (DV-Hop) 和多角度算法的概括.
  • 整合DV-Hop和多角度与结构修改,以平衡勘探和开发.
  • 整合水母搜索 (JS) 和人工子优化 (ARO) 算法,包括莱维飞行扰动和本地搜索,以提高收和精度.

主要成果:

  • 在16个不同的3D物联网环境中模拟性能.
  • 与使用平均平方错误 (MSE),规范化定位错误 (NLE),平均定位错误 (ALE) 和定位错误变异 (LEV) 度量标准的九个最先进的定位算法进行比较.
  • 通过定量相对改进比率测试,比竞争方法平均提高了39%的准确性.

结论:

  • 拟议的无GPS定位框架显著提高了3D物联网/EC环境中的定位精度.
  • 集成DV-Hop,JS和ARO算法为数据源本地化提供了强大而高效的解决方案.
  • 该框架有效地克服了GPS的局限性,为各种物联网和EC应用提供了切实可行的替代方案.