Pushing intelligence to the edge

We are already in the midst of a connected-device explosion, with research forecasting that we can look forward to seeing over 75 billion active IoT devices by 2025. From connected cars to smart meters to in-store beacons, companies are designing and deploying more and more objects intended to enhance the end-user experience and also create masses and masses of data.

However, all that new data needs gathering and managing and processing in real time in order to maximize its potential. How will that happen? Edge computing and fog computing, particularly edge, could be potential ways forward.

You will very likely hear a lot more about edge than fog computing, but what is it? In traditional cloud computing, data is stored and processed in a data center, but edge processes data at the edge of the network, in the devices that produce the data or conceivably in a local network. Conversely, fog computing exists in the computing region between the cloud and the edge, meaning it can perform some processing in the cloud and some in the edge devices.

One of the reasons for this is that sending the data transmitted by connected devices to and fro can take too long, and edge computing consumes far less network bandwidth. Processing it locally in the device or in a local network simply saves time. And with it estimated that the average end user will generate around 1.5Gb of data per day by 2020 and so many more devices connected to IoT generating data all the time, edge computing could give cloud computing vital support with the job of handling it all.

Supporting the growth of IoT

Both edge and fog refer to areas of the network where new IoT devices will live, generating and transmitting data, and both fog and edge use the computing power of those devices to perform tasks that would typically be carried out in the cloud. They both push data to analytics platforms to analyze it and convert it into usable information, and they do so in a way that helps companies reduce their cloud dependency.

Both edge and fog can help companies reduce dependence on cloud platforms to analyze data, consequently reducing latency in the network. Lower latency in turn means you can make data-driven decisions more quickly. Furthermore, since the edge devices have no storage capabilities, they cannot store data; so after the real-time processing is completed, the data is sent to the cloud where it can be stored and analytics can be performed on it.

What do you need edge and fog for?

Because you are going to be processing much more data. At present, enterprise network infrastructure concentrates largely on providing sufficient bandwidth to support all your remote applications, providing enough computing power in a remote cloud and unlimited storage for all your needs. That will change. Also, there is a need to utilize data in real time to maximize it, so that means processing it immediately, at the edge.

Moving forward, network environments will need to be more intelligent and capable of supporting a much bigger number of smart devices. Real-time intelligence to enable better decision-making means having that decision-making process closer to where data is generated. For a real-world example, picture autonomous vehicles being able to make their own quick-fire decisions or self-maintaining IoT-connected industrial equipment the same. Sensors placed in airplanes can generate real-time engine performance data that can be acted on proactively without the aircraft needing to come back down to earth to fix an issue. The cost reductions could be significant.

The more that companies push enterprise endpoints further outside of the traditional network, the more they will need to provide computing power and an intelligent environment to match.

Limits to growth

As our hunger for data increases, and with billions of devices connected to the Internet, faster, more reliable data processing will become essential.

Cloud has provided companies with cost efficiencies and greater flexibility, but the ongoing rise of IoT and mobile has continued to demand ever greater bandwidth. Fundamentally not every smart device needs cloud computing to operate, and in some cases it is a good idea to avoid sending data back and forth through the cloud. Edge can make organizations more agile and help you reduce costs, lower latency and just better control network bandwidth.

According to CB Insights' Market Sizing tool, the global edge computing market will be worth $6.72 billion by 2022. Companies might still be feeling their way into edge and fog, but you are certain to hear a lot more about them in 2019 and beyond.

In a rapidly changing digital world, the Internet of Things and data analytics are reshaping the way companies do business, whatever their size or activity. Find out more here.