Optimizing Adaptive Video Streaming: A Swarm Intelligence Approach to Dynamic Buffer Management

This paper presents a comprehensive exploration of the application of swarm optimization techniques in the context of adaptive video streaming, focusing on dynamic buffer management. Adaptive video streaming plays a pivotal role in delivering highquality multimedia content over variable network conditions. However, the dynamic nature of streaming environments poses challenges for buffer management, requiring efficient strategies to ensure uninterrupted playback. Swarm optimization algorithms, inspired by collective intelligence observed in natural systems, offer a promising approach to address these challenges. The paper delves into the fundamentals of swarm optimization, emphasizing its application to optimize parameters associated with buffer management, such as buffer size adjustments, bit rate selection, and adaptation policies. Through a review of case studies and experiments, the performance and effectiveness of swarm optimization in real-world scenarios are explored. Comparative analyses with traditional methods, integration with adaptive streaming protocols, and discussions on future trends and challenges contribute to a holistic understanding of the potential impact of swarm intelligence on the evolution of adaptive video streaming technologies. The findings presented in this paper pave the way for improved user experiences in multimedia streaming by leveraging the power of swarm optimization for dynamic buffer management