Cloud, Fog, or Edge: Where Should You Compute for AI?
As the digital landscape evolves, the question of where to execute computational tasks—whether on the cloud, at the edge, or within fog computing environments—becomes increasingly critical. In our recent study, we explored the performance and efficiency of these computing paradigms across various scenarios to help guide optimal decision-making. Video Encoding: The Power of the Edge Video encoding is a resource-intensive process that benefits significantly from low latency and high computational efficiency. Our research found that edge devices, particularly the latest generation of single-board computers like the Raspberry Pi 4 and Jetson Nano, excel in video-on-demand encoding. These devices reduce raw video transfer times and perform encoding tasks more efficiently compared to older models and some cloud instances. For continuous live stream encoding, cloud resources prove advantageous due to their lower encoding times, despite the potential for higher raw video transfer times. Cloud