Design of campus network optimization scheme based on SDN technology
基于 SDN 技术的校园网络优化方案设计

摘要

随着信息技术的快速发展，传统校园网络面临着诸多挑战，如带宽不足、管理复杂和安全隐患等。软件定义网络（SDN）作为一种创新的网络架构，通过分离控制层与数据层，为网络管理和优化提供了新思路。本文旨在设计和实现一个基于SDN技术的校园网应用，探索其在校园环境中的实际应用潜力，并通过实验验证其在网络性能与管理效率上的优势。研究首先构建了SDN网络模型，配置了控制器、交换机和终端设备。接着，利用Python开发了网络应用程序，并集成OpenFlow协议，实现网络流量的动态管理。选用Mininet搭建虚拟化实验环境，开展了流量调度、网络故障恢复、服务质量保证（QoS）和安全防护等场景的仿真实验。实验结果表明，基于SDN的校园网络在流量管理和资源分配方面显著优于传统网络架构，能够高效处理高峰流量并动态调整网络策略，有效预防拥堵。最后，本文结合实验数据，讨论了SDN在校园网络中的未来发展方向，并提出了包括智能化网络管理、边缘计算集成和基于AI的流量预测等优化建议，期望为校园网络的智能化和高效管理提供理论参考和实践指导。

Abstract

With the rapid development of information technology, the traditional campus network is facing many challenges, such as insufficient bandwidth, complex management and security risks. As an innovative network architecture, Software Defined Network (SDN) provides a new idea for network management and optimization by separating the control layer from the data layer. This paper aims to design and implement a campus network application based on SDN technology, explore its practical application potential in campus environment, and verify its advantages in network performance and management efficiency through experiments. Firstly, the SDN network model is constructed, and the controller, switch and terminal equipment are configured. Then, the network application program is developed by Python, and the OpenFlow protocol is integrated to realize the dynamic management of network traffic. Mininet is selected to build a virtualized experimental environment, and simulation experiments are carried out in traffic scheduling, network fault recovery, quality of service (QoS) and security protection. The experimental results show that the campus network based on SDN is significantly superior to the traditional network architecture in terms of traffic management and resource allocation, and it can efficiently handle peak traffic and dynamically adjust network strategies to effectively prevent congestion. Finally, based on the experimental data, this paper discusses the future development direction of SDN in campus network, and puts forward some optimization suggestions including intelligent network management, edge computing integration and AI-based traffic prediction, hoping to provide theoretical reference and practical guidance for intelligent and efficient management of campus network.