Augmented reality, fog, and vision: Duke professor outlines importance of smart architectures
An academic researcher’s talk on Monday at the Fog World Congress in San Francisco demonstrated both the limits of distributed computing structures and their critical importance to future IoT and augmented reality (AR) implementations.
Dr. Maria Gorlatova’s recent work has centered on the study of fog and edge architecture – specifically, the way in which particular methods of architecting those systems can affect latency and response time. She's studying the differences in systems which are on- and off-campus, that have different points of execution, which seems like the academic way of saying “where the computational work is done.”
The difference between the cloud – a highly centralized architecture – and fog computing, the industry’s current term of art for systems that have the abstracted nature of the cloud, but do their actual work much closer to the endpoint than the cloud’s faraway data centers – is immense. Both fog and its close cousin edge computing are useful alternatives to the cloud architecture.
“Fundamentally, our new devices that are generating high-bandwidth traffic and high-volume, high-velocity data just cannot afford to transfer all of the data to a centralized hub for processing,” Gorlatova said.
Some of the trade-offs, she said, are already fairly well-known. For instance, many tasks that aren’t terribly demanding from a compute or network perspective are best accomplished at the edge, but the advantages in terms of latency are outweighed by the cloud’s more potent computing capabilities for more complex tasks.
Some of the lessons from that research can seem self-evident, but they have wide-ranging implications. Gorlatova’s example was the security problem posed by bad actors influencing augmented reality systems – for example, creating huge, obtrusive holograms that block a user’s view of the real world, creating potentially serious safety issues.
Solutions to the vision-blocking problem, which was first described a year ago, center on fixed policy recommendations, which have to be implemented, manually, by human beings. By applying machine learning to the problem, however, an AR system could be taught to recognize when holograms are obstructing the view of a user, and simply move them out of the way, or make them transparent.
“Fog offers a natural chokepoint for reducing the resources consumed on mobile nodes in multi-user settings, as well as a natural point for making those experiences more intelligent.” She and her team are currently working on a fog-based pilot deployment for secure, responsive AR on Duke’s campus, and hopes to have a system in place early next year.
See the full story here: https://www.networkworld.com/article/3309446/cloud-computing/augmented-reality-fog-and-vision-duke-professor-outlines-importance-of-smart-architectures.html