| I'm not sure I completely grasped the air-traffic control example you mentioned, but I think you're on the same track, yep. Low-latency, localized computation within a well-connected physical area. To try to make it more concrete, here's a scenario: Imagine that smartphones are able to opt-in to become part of an edge cluster which communicates over some kind of local network fabric (be that wi-fi / 5G / similar). Now imagine that you have 2,000+ fans at a sporting event or live performance, all with their phones and many taking live recordings. Shifting high-fidelity video/audio data from that many devices at an event back to the cloud in realtime might not be particularly feasible and/or useful for various network contention, bandwidth, and latency reasons (both client and server-side). But if those devices were already running a containerized application to perform -- say, 3D image stitching[0], for example -- you could collect, compute and redistribute results via the cluster in near-real-time, potentially providing some pretty immersive audience experiences (3D highlights and replays and all kinds of interesting augmented reality interpolation of audience & performers). It'd also raise questions around who owns/authorizes the on-device computation, who has permission and copyright over the data captured, and various other issues. All very hypothetical ideas, but technically feasible. Predicting fast food order demand is much more practical challenge to begin with, no doubt :) [0] - https://www.geekwire.com/2013/microsoft-updates-photosynth-w... |