摘 要
随着物联网技术的快速发展，海量设备产生的数据对传统云计算架构提出了严峻挑战，边缘计算作为一种新兴的分布式计算范式，能够有效缓解集中式处理带来的网络带宽压力和延迟问题。本研究旨在探索边缘计算在物联网数据处理中的应用潜力及其优化策略，通过构建基于边缘节点的分布式数据处理框架，实现对物联网数据的实时分析与高效管理。研究采用理论分析与实验验证相结合的方法，首先从系统架构设计入手，提出一种融合边缘智能与数据预处理的新型框架；其次，针对边缘节点资源受限的特点，设计了动态任务分配算法以提升计算效率；最后，通过搭建模拟实验环境，验证所提方法在降低数据传输延迟、提高系统响应速度以及优化能耗方面的实际效果。实验结果表明，该框架能够在保证数据处理精度的同时显著减少云端负载，并实现边缘节点间的协同优化。本研究的主要创新点在于将边缘计算与物联网数据特性深度融合，提出了一种适应性强且可扩展的解决方案，为未来物联网应用场景下的数据处理提供了新思路和技术支持。
关键词：边缘计算；物联网数据处理；分布式框架；动态任务分配；边缘智能
Abstract
With the rapid development of Internet of Things (IoT) technology, the massive amount of data generated by a large number of devices poses significant challenges to traditional cloud computing architectures. Edge computing, as an emerging distributed computing paradigm, can effectively alleviate the network bandwidth pressure and latency issues caused by centralized processing. This study aims to explore the application potential and optimization strategies of edge computing in IoT data processing. By constructing a distributed data processing fr amework based on edge nodes, it enables real-time analysis and efficient management of IoT data. A combination of theoretical analysis and experimental validation is employed in this research. Starting with system architecture design, a novel fr amework integrating edge intelligence and data preprocessing is proposed. In response to the resource-constrained characteristics of edge nodes, a dynamic task allocation algorithm is designed to enhance computational efficiency. Finally, through the establishment of a simulated experimental environment, the practical effects of the proposed method in reducing data transmission latency, improving system response speed, and optimizing energy consumption are verified. The experimental results indicate that this fr amework can significantly reduce cloud load while ensuring data processing accuracy and achieve collaborative optimization among edge nodes. The main innovation of this study lies in the deep integration of edge computing with the characteristics of IoT data, proposing a highly adaptable and scalable solution that provides new ideas and technical support for data processing in future IoT application scenarios.
Keywords: Edge Computing；Internet Of Things Data Processing；Distributed fr amework；Dynamic Task Allocation；Edge Intelligence
目 录
摘 要 I
Abstract II
一、绪论 1
（一）边缘计算与物联网数据处理的研究背景 1
（二）边缘计算在物联网领域的研究现状分析 1
（三）本文研究方法与技术路线设计 2
二、边缘计算在物联网数据处理中的关键需求 2
（一）物联网数据处理的挑战与瓶颈 2
（二）边缘计算对实时性需求的支持 2
（三）边缘计算在数据隐私保护中的作用 3
三、边缘计算架构在物联网中的应用模式 4
（一）边缘节点部署与资源分配策略 4
（二）数据分流与边缘计算任务卸载机制 4
（三）边缘计算与云计算协同优化方案 5
四、边缘计算在典型物联网场景中的实践探索 5
（一）智能家居中边缘计算的数据处理应用 5
（二）工业物联网中的边缘计算性能评估 6
（三）智慧城市中边缘计算的技术实现路径 7
结 论 7
致 谢 9
参考文献 10
