You read that right by the way: fog. There is a link with cloud, again an important accelerator of IoT, but it’s less cloudy and more foggy. And it promises to accelerate IIoT developments. Fog computing is mainly important for the Industrial Internet of Things or IIoT anyway.
Fog computing: what and why?
Fog computing, the term comes from Cisco, is not a network technology. It’s a hybrid a system-level architecture approach whereby the possibilties of cloud computing and distributed processing and analytics power are brought to the edge of a network.
Simply said: instead of transporting all data over the network and then processing it, for instance in the cloud, some operations are performed close to the IoT device (endpoint) and application, hence the edge of the network or the endpoint, and processes IoT data faster but also without wasting bandwidth that can thus be saved. There’s a bit more to it but in a nutshell that is what it does.
Note by the way that edge computing, which fog computing is a form of, is not new.
Fog computing offers many benefits (avoiding the costs of ever more bandwidth, solving high latency on the network, less bottlenecks and a reduced risk of connectivity failures, which you really don’t want in IoT) and is gaining steam.
End 2015 a range of IoT leaders launched the OpenFog Consortium. The aim: accelerate the deployment of Fog technologies through the development of an open architecture as the press release stated. The founding partners are not the smallest and include (obviously) Cisco, ARM, Dell, Intel, Microsoft and Princeton University.
If you visit the site of the OpenFog Consortium, you’ll notice that on top of the founding members there’s a whole list of leading firms such as AT&T, GE Digital, Fujitsu, Schneider Electric, Toshiba and NTT Communications, to name a few, and a long list of universities and university-affiliated research labs or spin-offs.
Defining fog computing – dealing with collosal amounts of Internet of Things data the way it makes sense
Here is how the consortium defines fog computing:
“Fog computing is a system-level horizontal architecture that distributes resources and services of computing, storage, control and networking anywhere along the continuum from Cloud to Things. By extending the cloud to be closer to the things that produce and act on IoT data, fog enables latency sensitive computing to be performed in proximity to the sensors, resulting in more efficient network bandwidth and more functional and efficient IoT solutions. Fog computing also offers greater business agility through deeper and faster insights, increased security and lower operating expenses”.
A whole mouthful but it is indeed “big” for the Internet of Things so if you’re interested in IoT you absolutely should learn more about it.
Fog computing: many benefits but not always the best solution
In the meantime we’ll leave the last word, how else could we, to someone from Cisco who blogged at the occasion of the launch of the Fog Consortium and gave some examples of the possibilities of fog computing.
We quote: “Fog computing can provide immense value across all industries. For example, it might take 12 days via satellite to transmit one day’s worth of data to the cloud from a remote oil rig. With fog computing the data is processed locally, and safety or equipment alerts can be acted upon immediately”. More examples in the blog post.
Is fog always the best solution? No, there are circumstances where cloud computing is a better fit. It’s about striking the right balance and picking the best mix for the purpose of each different scenario. As it always is. But that’s for a later post.
Moreover, in an often cited White Paper from, yes, Cisco, entitled “Fog Computing and the Internet of Things: Extend the Cloud to Where the Things Are” the authors offer an overview of when to consider fog computing as you can read in the paper (PDF opens) (e.g. when data is collected at the extreme edge such as in ships, roadways or, closer, factory floors; when there is high data generation across a large geopgraphic area and of course when analyzing this data and acting upon it needs to happen really fast).
More on the IoT and cloud and fog computing dimension in the video below where the decentralization, which the IoT brings and how fog computing fits in it, is tackled.
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