Fog computing, also known as edge computing, has begun to take off. Fog computing is an intermediate layer that extends the cloud layer. As Giti Javidi, Ehsan Sheybani, and Lila Rajabion write in Focusing in on Fog Computing’s Implications for Business, “simply put, fog is a cloud close to the ground.” With fog architecture, some of the computing is moved to the edges, away from centralized data centers and cloud solutions, allowing data to be processed locally on smart devices rather than being sent to the cloud for processing.
Why are companies are turning to fog computing? According to Javidi and her coauthors, they are doing it for higher efficiency, better security, faster decision-making processes, and lowered operating costs. Internet of Things devices, in particular, can put a huge strain on the internet infrastructure. In their report, Javidi et al describe a case of fog computing that reduces that stress: A jet engine can create about 10 TB of performance and condition data in 30 minutes. Transmitting that data to the cloud and getting the response data back takes a lot of time and bandwidth, which introduces latency. Using a fog environment, the processing can take place on a local router, resulting in data that can be acted on in just milliseconds, in addition to sending data on to the cloud for historical analysis and longer-term storage.
While there are many benefits of fog, there are still also risks. For example, a major disaster could wipe out individual processors in a city, resulting in catastrophic data losses. However, suggests the research team, using fog and cloud computing in concert — getting efficiency from fog computing while storing data in the cloud to enable recovery from disruptions quickly — helps to allay this risk.
Fog computing is especially beneficial for applications that require a <1 second response time. Consider medical wearables, where a real-time response can be a literal life or death action. It’s also useful in less urgent cases, as Javidi et al describe:
A good example is found in the airline industry. When a plane lands, data from its engines is downloaded and analyzed. If any anomalies are discovered that could indicate trouble with the engine or any potential cause of failure, the problem must be remedied, usually by procuring and installing a new part. The entire process typically takes several hours. With fog computing, airlines have the capability to do all the analytics in-flight, on the plane, and to transmit any anomalies to the destination airport while still in the air. Then, when the plane lands, the needed part can be waiting, reducing downtime to 15 to 30 minutes rather than hours.”
You can see how industries with a lot of preventative maintenance needs could embrace fog computing to improve safety and efficiency.
For More on Fog Computing
Cutter Research: Cutter Consortium clients can read Focusing in on Fog Computing’s Implications for Business, as well as Fog Computing: A New Space Between Data and the Cloud (also by Giti Javidi, Ehsan Sheybani, and Lila Rajabion) to learn more about the ways fog computing enhances and complements the cloud by bringing the processing closer to a cluster of IoT devices, resulting in faster analytics.