Cloud-Edge Architecture for 4K 360-Degree Video Encoding in FoV-based Live DASH

The demand for immersive multimedia experiences has propelled the adoption of 4K 360-degree video streaming. However, delivering such high-resolution content imposes challenges related to bandwidth constraints and computational overhead. Adaptive streaming based on the user Field of View (FoV) offers a solution by providing high-quality video only in the viewed area and reducing the quality of peripheral regions, thereby optimizing bandwidth usage with low impact on user experience. This paper proposes a cloud-edge architecture for live encoding and streaming of 4K 360-degree videos using FoV-based adaptation within the Dynamic Adaptive Streaming over HTTP (DASH) framework. Leveraging cloud-native technologies like Kubernetes and Knative, the system employs a GPU-accelerated serverless architecture triggered by event-driven mechanisms. Experimental results demonstrate that the proposed system meets the latency requirements of live streaming, maintaining end-to-end processing times well below the 10-second threshold. Additionally, the adaptive streaming approach can achieve up to a 77% reduction in bandwidth consumption by adjusting the quality of video tiles based on the user’s FoV.