When Data is Bigger than Big: 5G, Edge Computing and IIoT

When we speak of some new technology becoming “big”, the discussion is all too often about amorphous factors like mindshare or hype. The rise of an Industrial Internet of Things (IIoT) will be big, but not just in adoption rate, or industry buzz. It will be big in the amount of data generated, processed, and consumed. We’re talking zettabytes big.

One zettabyte is equivalent to a billion terabytes or a trillion gigabytes. That’s a lot of new data that needs to be wrangled every second of every day. This much data will overwhelm your existing networks – bringing data movement and processing to a near standstill if not upgraded.

To make the vision of an ubiquitous Industrial Internet of Things (also known as Industry 4.0) not only possible but practical requires new ways to store, transmit, and process all that information. Two new technologies are key to successful IIoT deployment: 5G data transmission and Edge computing.

5G is more familiar, as it is now being deployed by cellular networks. 5G is for more than smartphones, it is also a data transmission standard that can be deployed for industrial purposes, similar to how WiFi is used by all aspects of society today. 5G uses millimeter wave bands and multiple input/output antenna arrays to achieve blazing speed — up to 20 gigabytes per second. That’s 10 times faster than the theoretical top speed of 4g wireless and hundreds of times faster than the typical WiFi network.

New business models are emerging to bring 5G to manufacturing, logistics, and other fast-moving, data-rich industries. Fixed wireless access (FWA), private network, and network slicing over public networks will all become more common as companies deploy IIoT infrastructure.

Edge computing is much less well known, but equally necessary. Simply put, it means data processing is decentralized. Instead of sensors on a piece of equipment gathering data and transmitting it to a server, equipment becomes capable of processing and acting on information locally. Think of it as hundreds of thousands of mini-CPUs scattered throughout your infrastructure and products.

“Edge” is the common term for two related computing technologies being rolled out for IIoT, Fog or Edge. A Fog computing environment runs at the level of the local area network. Data moves from endpoints to a gateway, and from there to more traditional industrial processing sources. Edge computing decentralizes the processing even more, as the individual devices are more capable of higher-level computation and direct machine-to-machine data use.

IIoT systems will use both Fog and Edge — depending on local variables — to deliver the needed integration between operations and IT. The goal is the deployment of smart-things technology in such a way as to decentralize computation as much as possible. If the IIoT were an organism, 5G and edge would be the nervous system; 5g is the signal and edge is the nerve and brain tissue.

Edge computing should be viewed as a complement to Cloud computing rather than as a competition. The interplay between Cloud and Edge devices can help to reduce energy consumption, reduce IT deployment redundancies, and improve quality of user experience.

Two fundamental transmission issues will make or break the use of such large data for IIoT, throughput and latency. Throughput is how much data can be transferred from Point A to Point B in a given amount of time. Latency is the time between stimulus and response. Throughput is more of a plumbing issue, so to speak; it is making the ‘pipes’ big enough to handle the data load. Latency is a function of how fast data can be processed on each end of the transaction.

Latency is like a golf score, lower numbers are better. The quality of service users experience will weigh heavily on latency factors. A delay of 100 milliseconds or less is considered acceptable for many tasks, such as real-time dashboards and remote CAD work. User experience tightly coupled to visual stimulus — including virtual reality — requires much lower latency times, ideally down to 20ms.

Where we go from here

IIoT really won’t be possible without the use of 5G and Edge/Fog computing. Once manufacturers open the door, they will discover opportunities to create new products, applications, services, and entire business models. Teleoperation of machines will be possible, along with other situations that rely on interface and control of real objects at a distance. Right now most networks are too slow to allow rich use of virtual reality, but that will change with new IIoT networks.

Product engineering teams wanting to design IIoT-aware products will need new software tools that provide both test bed utility and reference architecture for end users. As there are few 5G-savvy product engineers, it will be up to software companies to write software that provides the IIoT expertise engineering teams need.

Faster throughput and decentralized processing will be the foundation for widespread adoption of virtual, augmented, and mixed reality applications. The use of such “see it as if you were there” applications will offer ways to improve production efficiency, reduce production costs, and enhance product quality. The effects will ripple through the organization — from product design to manufacturing to maintenance — and on to the end user.

Editor’s Note: Interested in learning more about lIoT? Join Dassault Systèmes for 3DEXPERIENCE: A Virtual Journey, launching via live-stream on July 29th at 1:00 PM Eastern Time. 3DEXPERIENCE: A Virtual Journey will deliver thought-provoking and actionable content presented by a powerful line-up of industry influencers, customers and Dassault Systèmes experts.

The session called Industrial IoT in Challenging Times drops on July 29th as part of the Manufacturing and Industrial Engineering breakout. Register now

randall.newton@gmail.com'

Randall Newton

Randall S. Newton is Managing Director of Consilia Vektor, a boutique consulting firm serving the engineering software industry and related technologies. He is a Contributing Editor at Digital Engineering Magazine and AEC Magazine (UK). Mr. Newton has been in the engineering software industry since 1985 as a journalist, business analyst, publisher, programmer, and marketing consultant. His recent research explores the use of blockchain technology for industrial applications, and the rise of new design technologies for additive manufacturing.