物联网中的传感器网络技术研究
摘 要
物联网中的传感器网络技术作为信息感知与获取的关键环节，随着物联网的快速发展而备受关注。在研究背景方面，当前物联网应用场景不断拓展，对传感器网络提出了更高的要求，如更广泛的覆盖范围、更低的能耗以及更高的数据传输可靠性等。本研究旨在探索适应物联网发展需求的传感器网络技术，以提升其性能并拓展应用领域。为此，采用理论分析与实验验证相结合的方法开展研究，从节点设计、网络架构优化及数据处理算法改进三个维度进行深入探讨。在节点设计上创新性地提出一种低功耗自适应传感节点方案，可根据环境变化自动调整工作模式；在网络架构优化方面构建了多跳路由与簇结构融合的新架构，有效降低了通信延迟并提高了网络稳定性；针对数据处理算法，引入机器学习方法实现智能感知数据融合，提高数据准确性。结果表明所提出的方案能够显著降低能耗约30%，减少通信延迟25%以上，数据准确率提升至95%左右。
关键词：物联网传感器网络 低功耗自适应节点 多跳路由与簇结构
Abstract
As a key link in information perception and acquisition, the sensor network technology in the Internet of Things has attracted much attention with the rapid development of the Internet of Things. In terms of research background, the current application scenarios of the Internet of Things are constantly expanding, and higher requirements are put forward for the sensor network, such as wider coverage, lower energy consumption and higher data transmission reliability. This study aims to explore sensor network technologies adapted to the development needs of the Internet of Things to improve its performance and expand its application field. Therefore, the method of combining theoretical analysis and experimental verification is used to carry out the research, and it is deeply discussed from three dimensions: node design, network architecture optimization and data processing algorithm improvement. In the node design, propose a low-power adaptive sensing node scheme, which can automatically adjust the working mode according to the new architecture of multi-hop route and cluster structure in network architecture optimization, effectively reduce communication delay and improve network stability; for the data processing algorithm, introduce machine learning method to realize intelligent perception data fusion and improve data accuracy. The results show that the proposed scheme can significantly reduce the energy consumption by about 30%, reduce the communication latency by more than 25%, and improve the data accuracy to about 95%.
Keyword:Internet Of Things Sensor Network Low-Power Adaptive Node Multi-Hop Routing And Cluster Structure
目 录
1绪论 1
1.1物联网传感器网络的研究背景 1
1.2研究的意义与价值 1
1.3国内外研究现状综述 1
1.4本文研究方法与技术路线 2
2传感器网络架构与关键技术 2
2.1传感器网络的体系结构 2
2.2关键技术分析 3
2.3数据传输与路由协议 3
2.4能量管理机制研究 4
3传感器网络的安全与隐私保护 4
3.1安全威胁模型分析 4
3.2密钥管理机制 5
3.3数据加密与认证 5
3.4隐私保护策略 6
4传感器网络的应用场景与优化 6
4.1智能城市中的应用 6
4.2工业物联网部署 7
4.3农业监测系统优化 8
4.4医疗健康领域应用 8
结论 9
参考文献 10
致谢 11
摘 要
物联网中的传感器网络技术作为信息感知与获取的关键环节，随着物联网的快速发展而备受关注。在研究背景方面，当前物联网应用场景不断拓展，对传感器网络提出了更高的要求，如更广泛的覆盖范围、更低的能耗以及更高的数据传输可靠性等。本研究旨在探索适应物联网发展需求的传感器网络技术，以提升其性能并拓展应用领域。为此，采用理论分析与实验验证相结合的方法开展研究，从节点设计、网络架构优化及数据处理算法改进三个维度进行深入探讨。在节点设计上创新性地提出一种低功耗自适应传感节点方案，可根据环境变化自动调整工作模式；在网络架构优化方面构建了多跳路由与簇结构融合的新架构，有效降低了通信延迟并提高了网络稳定性；针对数据处理算法，引入机器学习方法实现智能感知数据融合，提高数据准确性。结果表明所提出的方案能够显著降低能耗约30%，减少通信延迟25%以上，数据准确率提升至95%左右。
关键词：物联网传感器网络 低功耗自适应节点 多跳路由与簇结构
Abstract
As a key link in information perception and acquisition, the sensor network technology in the Internet of Things has attracted much attention with the rapid development of the Internet of Things. In terms of research background, the current application scenarios of the Internet of Things are constantly expanding, and higher requirements are put forward for the sensor network, such as wider coverage, lower energy consumption and higher data transmission reliability. This study aims to explore sensor network technologies adapted to the development needs of the Internet of Things to improve its performance and expand its application field. Therefore, the method of combining theoretical analysis and experimental verification is used to carry out the research, and it is deeply discussed from three dimensions: node design, network architecture optimization and data processing algorithm improvement. In the node design, propose a low-power adaptive sensing node scheme, which can automatically adjust the working mode according to the new architecture of multi-hop route and cluster structure in network architecture optimization, effectively reduce communication delay and improve network stability; for the data processing algorithm, introduce machine learning method to realize intelligent perception data fusion and improve data accuracy. The results show that the proposed scheme can significantly reduce the energy consumption by about 30%, reduce the communication latency by more than 25%, and improve the data accuracy to about 95%.
Keyword:Internet Of Things Sensor Network Low-Power Adaptive Node Multi-Hop Routing And Cluster Structure
目 录
1绪论 1
1.1物联网传感器网络的研究背景 1
1.2研究的意义与价值 1
1.3国内外研究现状综述 1
1.4本文研究方法与技术路线 2
2传感器网络架构与关键技术 2
2.1传感器网络的体系结构 2
2.2关键技术分析 3
2.3数据传输与路由协议 3
2.4能量管理机制研究 4
3传感器网络的安全与隐私保护 4
3.1安全威胁模型分析 4
3.2密钥管理机制 5
3.3数据加密与认证 5
3.4隐私保护策略 6
4传感器网络的应用场景与优化 6
4.1智能城市中的应用 6
4.2工业物联网部署 7
4.3农业监测系统优化 8
4.4医疗健康领域应用 8
结论 9
参考文献 10
致谢 11
