摘 要
无线传感器网络（Wireless Sensor Networks, WSNs）在环境监测、智能交通和医疗健康等领域具有广泛应用，但其资源受限特性对数据融合与传输优化提出了严峻挑战。为提高网络性能并延长生命周期，本研究聚焦于WSNs中数据冗余消除与能量高效传输问题，提出了一种基于分布式协作的数据融合与传输优化框架。该框架通过引入分层聚类算法实现节点能耗均衡，并结合压缩感知理论设计了自适应数据采样机制，从而有效降低数据传输量。同时，针对多跳传输中的路径选择问题，提出了一种综合考虑链路质量与剩余能量的路由优化策略，显著提升了数据传输的可靠性和效率。实验结果表明，所提方法在减少通信开销的同时，能够显著延长网络寿命并保持较高的数据精度。此外，本研究还开发了一种动态调整机制，可根据网络负载变化实时优化参数配置，进一步增强了系统的鲁棒性与适应性。总体而言，本研究不仅为WSNs的数据处理与传输提供了新的思路，还为相关领域的实际应用奠定了理论基础，其创新点在于将分布式计算与节能传输有机结合，实现了性能与能耗的双重优化。
关键词：无线传感器网络；数据融合与传输优化；分布式协作；压缩感知；路由优化策略
Wireless Sensor Networks (WSNs) have been widely applied in environmental monitoring, intelligent transportation, and healthcare, among other fields. However, the resource-constrained nature of WSNs poses significant challenges for data fusion and transmission optimization. To enhance network performance and extend its lifecycle, this study focuses on the issues of data redundancy elimination and energy-efficient transmission in WSNs, proposing a distributed collaborative fr amework for data fusion and transmission optimization. This fr amework achieves balanced node energy consumption through the introduction of a hierarchical clustering algorithm and designs an adaptive data sampling mechanism based on compressive sensing theory, effectively reducing the volume of data transmission. Additionally, to address path selection problems in multi-hop transmission, a routing optimization strategy is proposed that comprehensively considers link quality and residual energy, significantly improving the reliability and efficiency of data transmission. Experimental results demonstrate that the proposed method not only reduces communication overhead but also substantially prolongs network lifetime while maintaining high data accuracy. Furthermore, this research develops a dynamic adjustment mechanism capable of optimizing parameter configurations in real-time according to network load variations, thereby enhancing the robustness and adaptability of the system. Overall, this study provides new insights into data processing and transmission in WSNs and lays a theoretical foundation for practical applications in related fields. Its innovation lies in the integration of distributed computing and energy-saving transmission, achieving dual optimization in both performance and energy consumption.
Keywords: Wireless Sensor Network; Data Fusion And Transmission Optimization; Distributed Collaboration; Compressive Sensing; Routing Optimization Strategy
目 录
1绪论 1
1.1无线传感器网络的研究背景与意义 1
1.2数据融合与传输优化的国内外研究现状 1
1.3本文研究方法与技术路线 2
2数据融合算法分析与优化 2
2.1数据融合的基本原理与框架 2
2.2基于压缩感知的数据融合算法 3
2.3融合算法中的能耗优化策略 3
2.4数据冗余与精度权衡的优化方法 4
2.5算法性能评估与实验验证 4
3数据传输机制设计与优化 5
3.1无线传感器网络传输特性分析 5
3.2多跳传输中的路由优化策略 5
3.3基于QoS的数据传输模型构建 6
3.4动态带宽分配与负载均衡方法 6
3.5传输延迟与可靠性优化研究 7
4融合与传输的协同优化策略 7
4.1协同优化的基本概念与目标 8
4.2数据融合与传输的联合建模方法 8
4.3能耗驱动的协同优化算法设计 9
4.4实时性约束下的协同优化方案 9
4.5协同优化的实际应用案例分析 10
结论 10
参考文献 12
致 谢 13
