With the explosion of the Internet of Things, connected devices are collecting more and more information through sensors, cameras, accelerometers, LiDAR, and depth sensors. Connected products are inherent in all kinds of industries from manufacturing to automotive, health tech, energy, utilities, and wearable tech. Aided by the convergence of AI and 5G, the quantity of data being collected is only expanding. It's estimated that a fully autonomous car will encompass over 60 microprocessors and sensors and generate more than 300 terabytes of data per year. Or, conversely, in an hour-long trip, up to 25GB of information will be sent to and from a connected vehicle (equivalent to about 100 hours of video).

With these massive quantities, capturing, aggregating, and analyzing data becomes a challenge. Not all data is useful, yet time-sensitive data such as autonomous vehicles, noxious gas monitoring, healthcare, and safety equipment is at risk of lag. A split-second delay of data (derived from, for example, a car being unable to identify a pedestrian on the road, or a malfunctioning insulin pump) going to the cloud and back to the device could be disastrous or deadly. Other data sites face the challenge of a location where the use of IoT in rugged environments, such as an offshore oil refinery, underground mine, or deep water well can result in unstable links with limited bandwidth and variable latency. Arguably less life or death, a virtual reality hangout would be less than immersive with poor data processing.

Edge computing is a concept with so many definitions according to industry and use cases that the Open Glossary of Edge Computing was created under the stewardship of The Linux Foundation, a community-driven process to develop and improve upon the terminology.

As the Linux Foundation explains, edge computing is:

"The delivery of computing capabilities to the logical extremes of a net- work in order to improve the performance, operating cost, and reliability of applications and services. By shortening the distance between devices, the cloud resources that serve them, and also reducing network hops, edge computing mitigates the latency and bandwidth constraints of today's Internet, ushering in new classes of applications.

In practical terms, this means distributing new resources and software stacks along the path between today's centralized data centers and the increasingly large number of devices in the field, concentrated, in particular, but not exclusively, near the last mile network, on both the infrastructure and device sides."

This is a preview of the Edge Computing Refcard. To read the entire Refcard, please download the PDF from the link above.