Online Video Streaming Application: A MERN Stack Implementation with Adaptive Bitrate Streaming and Edge Computing Optimization

Online Video Streaming Application: A MERN Stack Implementation with Adaptive Bitrate Streaming and Edge Computing Optimization

Mr. Byregowda, Associate Prof, SMVIT,

Rohit Rathore, Student, SMVIT,

Saakshi, Student, SMVIT,

Shrinivas, Student, SMVIT,

Vanktesh Dixit, Student, SMVIT

Abstract—

The exponential growth in video content consumption has necessitated the development of robust, scalable streaming platforms capable of delivering high-quality content across diverse network conditions and devices. This paper presents a comprehensive implementation of an online video streaming application utilizing the MERN (MongoDB, Express.js, React.js, Node.js) technology stack, enhanced with adaptive bitrate streaming through HTTP Live Streaming (HLS) protocol and intelligent edge computing optimization. Our system integrates FFmpeg for real-time video transcoding, AI-driven bitrate prediction algorithms, and edge caching mechanisms to address critical challenges in modern video delivery including latency reduction, bandwidth optimization, and scalability. Experimental results demonstrate a 30% reduction in latency compared to baseline implementations, 70% fewer buffering incidents through adaptive quality switching, and stable performance under concurrent loads of up to 10,000 users. The proposed architecture showcases the practical integration of modern JavaScript technologies with advanced streaming protocols, providing a foundation for next-generation content delivery platforms.