摘 要：随着网络规模的不断扩大和流量需求的快速增长，如何通过优化算法提升网络性能成为研究热点。本研究基于图论方法，探讨在网络流量优化中的策略设计与实现，旨在解决传统优化方法在复杂网络环境中效率低下及资源分配不均的问题。研究采用图论模型将网络拓扑结构抽象为节点与边的集合，并结合最短路径算法、最大流最小割理论以及动态规划方法，提出了一种改进的多目标流量分配策略。该策略能够有效平衡网络负载并降低传输延迟。实验结果表明，所提方法在大规模网络场景下显著提升了带宽利用率和数据传输效率，相较于现有方案平均性能提升约15%。本研究的主要创新点在于将动态权重调整机制引入图论模型中，实现了对实时流量变化的快速响应，同时为复杂网络环境下的流量优化提供了新的理论支持和实践指导。
关键词：网络流量优化；图论模型；多目标流量分配；动态权重调整；带宽利用率
Strategy Analysis of Graph Theory in Network Traffic Optimization
英文人名
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Abstract：With the continuous expansion of network scale and the rapid growth of traffic demand, how to improve network performance through optimization algorithms has become a research hotspot. This study explores the design and implementation of strategies for network traffic optimization based on graph theory methods, aiming to address the issues of low efficiency and uneven resource allocation in traditional optimization approaches within complex network environments. By employing a graph theory model, the network topology structure is abstracted as a set of nodes and edges, and an improved multi-ob jective traffic allocation strategy is proposed by integrating shortest path algorithms, maximum flow minimum cut theory, and dynamic programming methods. This strategy effectively balances network loads and reduces transmission delays. Experimental results demonstrate that the proposed method significantly enhances bandwidth utilization and data transmission efficiency in large-scale network scenarios, achieving an average performance improvement of approximately 15% compared to existing solutions. The primary innovation of this study lies in introducing a dynamic weight adjustment mechanism into the graph theory model, enabling rapid responses to real-time traffic changes and providing new theoretical support and practical guidance for traffic optimization in complex network environments.
Keywords: Network Traffic Optimization；Graph Theory Model；Multi-ob jective Traffic Allocation；Dynamic Weight Adjustment；Bandwidth Utilization
目 录
引言 1
一、图论基础与网络流量优化 1
(一)图论基本概念概述 1
(二)网络流量优化问题定义 2
(三)图论在网络优化中的适用性 2
二、最短路径算法在流量优化中的应用 3
(一)最短路径算法原理分析 3
(二)基于路径算法的应用 3
(三)最短路径算法的实际案例研究 4
三、流量均衡与图的最大流模型 4
(一)最大流问题的基本理论 4
(二)最大流算法在网络负载均衡中的作用 5
(三)实验验证最大流模型的优化效果 5
四、动态网络环境下的图论策略改进 6
(一)动态网络特性与挑战 6
(二)自适应图论算法的设计思路 6
(三)改进算法在实际场景中的应用分析 7
结论 7
参考文献 9
致谢 9
