We live in a connected world where we can control devices such as door locks, thermostats, sprinkler systems, cameras, and lights – all from our mobile devices and thanks to the power of the cloud. We’ve discussed the cloud in detail before, but simply put, it allows us to access and store data over the Internet instead of using local storage and computing. For many things the cloud is ideal. It saves costs on physical resources, provides efficiencies, and is flexibility, however, it does have its limitations, and this is where fog computing comes into play.
Fog computing lives on the edge of network as an extension of the cloud, or from a diagram perspective, closer to the ground (just like actual fog), between the cloud and the user. By utilizing edge devices such as routers, switches, integrated access devices (IADs) – basically any network device that connects an internal local area network (LAN) with an external wide area network (WAN) – fog computing allows for faster connectivity, better mobility support, less demand for bandwidth (data is aggregated at certain points, instead of sending over cloud channels), and a more secure network.
(Image from IoT Labs)
In contrast, as more nodes are added to the network, sending data back and forth from the cloud will create latency issues, limited bandwidth, and security issues – all while requiring high-speed internet connectivity.
Fog computing is ideal in situations where sending data to the cloud for processing and analysis would negatively affect performance and where connectivity is intermittent, like rural areas. One of the strongest cases for cloud computing comes from the automobile industry. According to a report from ON World, it’s expected that there will be 300 million connected cars on the road by 2025. These vehicles will use a range of sensors and automated systems for everything from self-driving/ self-parking to infotainment and traffic/ weather alerts. It wouldn’t be feasible to send the amount of data that these systems generate to the cloud.
Other applications for fog computing include reducing traffic congestion, drone delivery, video surveillance, smart buildings, and subsurface imaging – all of which require real-time data. By being able to support multiple industry verticals and applications through the network edge, systems become more flexible, cost-efficient, secure, and scalable. And it’s why fog computing is emerging as the top choice for bridging the gap between IoT devices and the cloud.