无线网络中的拥塞控制技术研究 -计算机科学与技术专业

摘要

随着无线网络的广泛应用，拥塞控制成为保障网络性能的关键问题。本研究旨在深入探讨无线网络环境下的拥塞控制技术，针对传统算法在网络动态性、资源受限性等方面的不足，提出一种基于智能预测与自适应调整的拥塞控制机制。该方法融合了机器学习中的深度强化学习算法，通过构建仿真模型对网络流量进行实时监测与预测，根据预测结果动态调整传输速率，有效避免网络拥塞。实验结果表明，所提方法在提高网络吞吐量、降低丢包率方面较现有方案有显著提升，特别是在高负载和复杂环境下优势明显。此外，该研究还分析了不同应用场景下算法的适用性，为无线网络拥塞控制提供了新的思路与方法，其创新之处在于将智能预测融入拥塞控制过程，实现了更精准的流量管理，为未来无线网络的发展提供了理论支持和技术参考。

关键词：无线网络拥塞控制；智能预测；自适应调整

Abstract

With the widespread application of wireless networks, congestion control has become a critical issue for ensuring network performance. This study aims to explore congestion control techniques in wireless network environments, addressing the limitations of traditional algorithms in terms of network dynamics and resource constraints by proposing an intelligent prediction and adaptive adjustment-based congestion control mechanism. The method integrates deep reinforcement learning algorithms from machine learning, employing a simulation model to conduct real-time monitoring and prediction of network traffic, dynamically adjusting transmission rates based on predictive outcomes to effectively prevent network congestion. Experimental results demonstrate that the proposed method significantly improves network throughput and reduces packet loss rates compared to existing solutions, particularly under high-load and complex conditions. Furthermore, this research analyzes the applicability of the algorithm in different application scenarios, providing new insights and methods for wireless network congestion control. Its innovation lies in incorporating intelligent prediction into the congestion control process, achieving more precise traffic management and offering theoretical support and technical references for the future development of wireless networks.

Keywords: Wireless Network Congestion Control；Intelligent Prediction；Adaptive Adjustment

摘要 I

Abstract II

一、绪论 1

（一）无线网络拥塞控制的研究背景与意义 1

（二）拥塞控制技术的国内外研究现状 1

二、无线网络拥塞成因分析 2

（一）网络拓扑结构对拥塞的影响 2

（二）数据传输特性与拥塞关系 2

（三）用户行为模式对拥塞的作用 3

三、拥塞控制算法原理及应用 3

（一）基于速率控制的拥塞算法 3