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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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在机会主义物联网系统中,用于最佳路由的上下文感知信任预测.

Abdulkadir Abdulahi Hasan1, Xianwen Fang1, Sohaib Latif2

  • 1School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan 232001, China.

Sensors (Basel, Switzerland)
|June 27, 2025
PubMed
概括
此摘要是机器生成的。

本研究引入了在社会机会主义物联网 (SO-IoT) 网络中安全数据路由的新框架. 它通过结合社交连接和可靠的节点行为来增强数据传输和信任准确性.

关键词:
贝叶斯的推理 贝叶斯的推理物联网安全物联网安全物联网安全杰弗里的条件是条件.社会机会主义的物联网 (SO-IoT)语境意识的沟通沟通是意识到背景的沟通.中间节点的选择选择.可靠性的可靠性路线优化路线优化安全的数据传播和安全的数据传播.单跳路由是一个单跳路由.社会利益 社会利益 社会利益基于信任的路由方式.值得信赖的信任级计算

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科学领域:

  • 计算机科学 计算机科学
  • 网络工程 网络工程
  • 人工智能的人工智能

背景情况:

  • 社会机会主义物联网 (SO-IoT) 网络通过物理和社会互动促进移动,临时设备通信.
  • 在SO-IoT中,有效的路由依赖于选择可靠的中间节点,以确保安全和高效的数据传播.
  • 现有的路由方法往往不足,因为它们只关注可靠性或社会利益,忽视了多方面的节点可信度.

研究的目的:

  • 为SO-IoT环境提出一种新的基于信任的路线优化框架.
  • 为全面的节点可信度评估整合社会利益和行为可靠性.
  • 提高动态SO-IoT网络中的数据传播安全性和效率.

主要方法:

  • 开发了一个基于信任的路线优化框架,利用贝叶斯推理和杰弗里的条件.
  • 基于集成的社会和行为指标计算了中间节点的复合信任级别.
  • 通过场景驱动的评估和大规模的NS-3模拟进行了两阶段的模拟分析.

主要成果:

  • 拟议的框架实现了高达88.9%的交付率.
  • 与基准路由方案相比,证明了最小的能源消耗.
  • 在模拟结果中达到最高的信任准确率为86.5%.

结论:

  • 拟议的基于信任的框架对于现实世界SO-IoT应用程序来说是强大的和可扩展的.
  • 整合社会利益和行为可靠性显著提高了路由性能.
  • 该模型为SO-IoT中安全和高效的数据转发提供了一种优越的节点选择方法.