Conferences and supporting programme
Challenges of Visual Fog Computing
The visual fog paradigm envisions tens of thousands of camera-enabled edge devices, providing collaboratively live sensing for a myriad of applications. The scale needed necessitates orchestration that offloads intelligently workloads to devices. In this presentation, we will cover challenges in visual fog computing and our pioneered study in offloading and orchestration.
The visual fog paradigm envisions tens of thousands of heterogeneous, camera-enabled edge devices distributed across the Internet, providing live sensing for a myriad of different visual processing applications. The scale, computational demands, and bandwidth needed for visual computing pipelines necessitates offloading intelligently to distributed computing infrastructure, including the cloud, Internet gateway devices, and the edge devices themselves. We focus the presentation in the two aspects of visual fog orchestration: offloading and scheduling. Offloading is a mechanism for realizing (live) workload migration, whereas scheduling is the problem of assigning the visual computing tasks to various devices to optimize network utilization. In our pioneered study, we demonstrate sub-minute computation time to optimally schedule 20,000 tasks across over 7,000 devices, and just 7-minute execution time to place 60,000 tasks across 20,000 devices. By showing our approach is ready to meet the scale challenges, visual fog is feasible and a viable paradigm to scale out video analytics systems.
--- Date: 28.02.2018 Time: 2:30 PM - 3:00 PM Location: Exhibitor's Forum hall 3A, stand 3A-610