Swarm intelligence, inspired by natural systems such as ant colonies and bird flocking, offers a powerful approach to optimizing video data distribution in edge networks. As video streaming services expand, the need for efficient bandwidth usage and low-latency delivery becomes critical, particularly in edge-driven environments. This chapter explores the application of swarm intelligence algorithms, such as Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO), to enhance video streaming performance in edge networks. These algorithms help in dynamically managing network resources, optimizing video routing, and reducing delays in video transmission. The role of edge computing in improving video quality, especially in remote and bandwidth-limited regions, is also discussed. Edge-based video caching and computation offloading are highlighted as key techniques that, when combined with swarm intelligence, can greatly improve the Quality of Service (QoS) in real-time video delivery. Through case studies and performance evaluations, the chapter demonstrates how swarm intelligence can effectively reduce network congestion, improve load balancing, and ensure scalable, high-quality streaming experiences. As demand for high-definition video content continues to grow, swarm intelligence is poised to play a pivotal role in the future of edge-based video streaming.