Fog Computing: a New IoT Architecture? Posted on : Aug 19 - 2017

Just like the cloud, fog computing is expected to open new business models. But what is it?

It’s still the early days for the Internet of Things, and many people assume it is being structured like a mechanical flower, with devices and sensors feeding data into central hubs that run sophisticated analytics and algorithms in a back room.

The IoT may not look that way at all.

Rather, the IoT may more likely be supported by “fog computing,” in which computing, storage, control and networking power may exist anywhere along the architecture, either in data centers, the cloud, edge devices such as gateways or routers, edge equipment itself such as a machine, or in sensors.

Traditional networks, which feed data from devices or transactions to a central storage hub—the old “data warehouse” model—can’t keep up with the data volume and velocity created by IoT devices. Nor can the data warehouse model meet the low latency response times that users demand.

The cloud was supposed to be an answer. But sending the data to the cloud for analysis also poses a risk of data bottlenecks, as well as security concerns. New business models, however, need data analytics in a minute or less (with some use cases of even less than a second). The problem of data congestion will only get worse as IoT applications and devices continue to proliferate.

What Is Fog Computing?

Fog computing – a term originally coined by Cisco—is in many ways synonymous with edge computing. In contrast to the cloud, fog platforms have been described as dense computational architectures at the network’s edge. Characteristics of such platforms reportedly include low latency, location awareness and use of wireless access. Benefits include real-time analytics and improved security.

While edge computing or edge analytics may exclusively refer to performing analytics at devices that are on, or close to, the network’s edge, a fog computing architecture would perform analytics on anything from the network center to the edge.

One use case for fog computing is a smart traffic light system, which can change its signals based on surveillance of incoming traffic to prevent accidents or reduce congestion. Data could also be sent to the cloud for longer-term analytics.

Other cases described by Cisco might include rail safety; power restoration from a smart grid network; and cybersecurity. PrismTech Vortex cites use cases with connected cars (for vehicle-to-vehicle and vehicle-to-cloud communication); and in smart city applications, such as intelligent lighting and smart parking meters. In the figure below, Cisco shows what kinds of analytics could be performed along a fog network View More