Research on the Application of Software-Defined Networking in Enhancing the User Experience of Tourism E-Commerce

With the rapid development of tourism e-commerce, user demands are becoming increasingly diversified and personalized with higher requirements for service quality and experience. Traditional networks can no longer meet these needs. Therefore, this study introduces software-defined networking (SDN) into a platform and improves its model by integrating genetic algorithms, reinforcement learning, and unsupervised learning methods. Experimental results showed that the optimized SDN-based model provided a more reasonable, flexible, and balanced controller deployment mechanism, improving overall network performance. Additionally, it enhanced abnormal traffic detection accuracy, achieved traffic balance among different servers, and reduced average server latency. To better meet personalized user needs, the proposed video stream quality of service optimization scheme improved the video viewing experience. Experimental results demonstrated the model's superior network performance and effective support for tourism e-commerce platforms.