摘 要
随着物联网设备的广泛部署，海量数据的实时处理成为亟待解决的问题。传统云计算模式难以满足低延迟、高带宽和隐私保护等需求，基于边缘计算的物联网数据处理框架应运而生。本研究旨在构建一种高效、灵活且可扩展的边缘计算架构，以优化物联网数据处理流程。通过在靠近数据源的边缘节点进行数据预处理与分析，有效减轻云端负载并提升响应速度。研究采用分层式架构设计，将边缘节点划分为感知层、处理层和服务层，各层之间通过标准化接口实现无缝对接。创新性地引入了自适应任务调度算法，根据网络状态和计算资源动态分配任务，确保系统性能最优。实验结果表明，在多种典型应用场景下，该框架能够显著降低数据传输延迟，提高数据处理效率达30%以上，并有效保障数据安全与隐私。此外，提出的轻量级数据压缩与加密机制进一步增强了系统的实用性和可靠性。本研究为物联网环境下边缘计算的应用提供了理论依据和技术支持，对推动智能城市建设具有重要意义。
关键词：边缘计算；物联网数据处理；自适应任务调度；数据安全与隐私；轻量级数据压缩与加密
Abstract
With the widespread deployment of Internet of Things (IoT) devices, real-time processing of massive data has become an urgent issue. Traditional cloud computing models struggle to meet the demands for low latency, high bandwidth, and privacy protection, leading to the emergence of edge computing-based IoT data processing fr ameworks. This study aims to construct an efficient, flexible, and scalable edge computing architecture to optimize the IoT data processing workflow. By conducting preprocessing and analysis of data at edge nodes close to the data sources, this approach effectively alleviates the load on the cloud and enhances response speed. A hierarchical architecture design is adopted, dividing edge nodes into perception, processing, and service layers, with seamless integration achieved through standardized interfaces between layers. An innovative adaptive task scheduling algorithm is introduced, dynamically allocating tasks based on network conditions and computational resources to ensure optimal system performance. Experimental results demonstrate that under various typical application scenarios, this fr amework significantly reduces data transmission latency and improves data processing efficiency by over 30%, while effectively ensuring data security and privacy. Additionally, the proposed lightweight data compression and encryption mechanisms further enhance the practicality and reliability of the system. This research provides theoretical foundations and technical support for the application of edge computing in IoT environments, playing a significant role in promoting the development of smart cities.
Keywords：Edge Computing；Internet Of Things Data Processing；Adaptive Task Scheduling；Data Security And Privacy；Lightweight Data Compression And Encryption
目 录
摘 要 I
Abstract II
引 言 1
第一章 边缘计算与物联网概述 2
1.1 物联网发展现状 2
1.2 边缘计算基本概念 2
1.3 边缘计算在物联网中的作用 3
第二章 数据处理框架设计原则 5
2.1 框架设计目标 5
2.2 关键技术需求 5
2.3 系统架构模型 6
第三章 数据采集与预处理机制 8
3.1 数据源分析 8
3.2 数据采集方法 8
3.3 数据预处理策略 9
第四章 数据传输与存储优化 11
4.1 传输协议选择 11
4.2 存储方案设计 11
4.3 资源分配算法 12
结 论 14
参考文献 15
致 谢 16
