A framework for visual fog computing
Shao‐Wen Yang, Omesh Tickoo, Yen-Kuang Chen · 2017
Visual data are rich, which have opened vast analytics opportunities and been widely used in many applications. However, the demanding requirements of computational resources and bandwidth have prevented the data from being useful in an economically efficient manner. A visual fog paradigm is needed for efficient processing of continuous video streams by collaboratively using things in the Internet of Video Things (IoVT), comprising edge devices, intermediate gateways, and servers on premise or in the cloud, as the computing platform. The challenges lying ahead include (1) Reusability-a reusable framework across multiple vertical applications, (2) Efficiency-the intelligence for online distributing and redistributing work-load for optimal system performance, and (3) Configurability-the user interface for (layperson) users to easily analyze the visual data as well as the corresponding metadata. This paper spells out the need of a framework for visual fog computing and suggest promising research directions towards instantiations of a visual fog computing framework.