Fog Computing has recently emerged as the paradigm to address the needs of edge computing in Internet of Things (IoT) and Industrial Internet of Things (IIoT) applications.
Cisco's Ginny Nichols originally coined the term Fog Computing. The metaphor comes from the fact that fog is cloud close to the ground, just as fog computing concentrates processing at the edge of the network. In Fog computing data processing and applications are concentrated in devices at the network edge rather than existing almost entirely in the cloud. That concentration means that data can be processed locally in smart devices rather than being sent to the cloud for processing.
In the IoT scenario, things at the edge can create significantly large amounts of data. Transmitting all that data to the cloud and transmitting response data back puts a great deal of demand on bandwidth, requires a considerable amount of time and can suffer from latency issues. In a Fog Computing environment, much of the processing would take place closer to the edge in a router device, rather than having to be transmitted to the Cloud.
Fog Computing extends the Cloud Computing paradigm to the edge of the network. While fog and cloud use the same resources (networking, compute, and storage) and share many of the same mechanisms and attributes (virtualization, multi-tenancy) the extension is a non-trivial one in that there exists some fundamental differences stemming from the reason Fog Computing was developed: to address applications and services that do not fit the paradigm of the Cloud.
Vortex DDS seamlessly supports both the Cloud and Fog Computing paradigm with native support for device-to-device and device-to-cloud communication. Vortex Fog is an ideal solution to enable Fog Computing Architectures allowing devices to communicate peer-to-peer, efficently share / store data and take local decisions.