Key Drivers for Growth of the Edge

This Industry Viewpoint was authored by Keith Rutledge, General Manager of Compass EdgePoint

This is the second in a two-part series about trends that are accelerating the adoption of edge infrastructure and broadening the use cases of edge computing. In Part 1, I focused on how the COVID-19 pandemic is driving the need for edge computing in a way that I believe will continue after the pandemic subsides This column builds on that discussion by discussing other trends that are playing a major role in the need for far more edge infrastructure.

IoT is the biggest factor driving the edge deployments I am currently seeing. That is because IoT networks are often best served by edge assets for a variety of reasons, including cost and performance. IoT will continue to be a major driver – especially given the growth projections for the number of IoT devices that are being deployed – but IoT is not alone. Other factors that will accelerate edge implementations and that will broaden their geographic reach include augmented and virtual reality, driverless cars and smart city initiatives.

Virtual/Augmented Reality

When most people think of virtual reality, they envision gamers wearing devices like Oculus Rift or Samsung Gear VR – which provide online game players with immersive experiences. These gaming devices are growing in popularity and rely on very high bandwidth and low latency in order to deliver the user experience that gamers are expecting. As the number of users continues to grow and as virtual reality gaming demands ever-higher performance, centralized infrastructure cannot effectively support these applications. Edge computing that moves infrastructure far closer to end users is critical to making VR/AR perform as needed.

This is not simply about gaming, though. Virtual and augmented reality is also being adopted in a wide range of industries ranging from public safety to construction to manufacturing. As an example, augmented reality will provide firefighters in a burning building with pathfinding on their face shields, helping them navigate the floorplan even in smoke-filled rooms as they make rescues. Engineers and construction workers will use VR and AR systems to make construction sites safer while also assisting with precise and more efficient construction. There are also exciting applications involving healthcare and education that would potentially involve large-scale implementations.

All of these consumer applications and business applications have a single thing in common: the need for nearby edge computing assets that reduce latency by moving the functionality as close as possible rather than relying on centralized data centers and network infrastructure.

Driverless Cars and Augmented Drivers

Although developing cars that can safely operate without a driver is taking a little longer than many proponents have predicted, the day that the vehicle that just cut you off has no one in the driver’s seat is coming, and they’ll be generating a lot of data. Hitachi Data Systems estimates that a single driverless vehicle will create more than 25GB/hour.

But it’s not just driverless cars driving this need. In parallel to truly autonomous vehicles, augmented driver applications are growing rapidly and have similar needs for widespread infrastructure that is located as close as possible to where those cars and trucks are driving. These applications provide real-time information to assist driver much like the Augmented Reality applications discussed earlier in this article.

All of these vehicular systems require robust edge computing infrastructure in addition to their onboard computers. Edge facilities could be used to analyze vehicle-generated data to identify and predict problems to provide for more timely and less disruptive preventive maintenance. Other data generated can be used to investigate things like traffic flow by daypart to enable more effective road design and traffic light timing to make everyone’s morning commute just a little more pleasurable. 

Smart Cities

The last driver for growth of the edge that I will discuss are smart city deployments, which will involve an enormous number of connected devices in the form of smart meters on residential homes, smart electrical grid applications, energy-efficiency controls in commercial buildings, more efficient control of traffic signals, environmental sensors and much more. These devices are being deployed in metro areas across the country by energy utilities, municipal agencies, urban planning authorities, building owners, homeowners, public safety agencies and others – and all of this smart city equipment will require edge computing infrastructure that is local.

Centralized data centers or clouds are not able to effectively support these implementations because of the massive data volume produced by tens of thousands, hundreds of thousands or millions of interconnected devices. As, a result edge data centers will be located throughout the municipality, serving as the primary point of information processing while forwarding large chunks of data to the cloud for storage and higher level processing.

Each of the three types of applications I’ve discussed in this article requires ultra-low latency and robust computing infrastructure that is local rather than located in a distant location that backhauls data back and forth to centralized data centers. Combined with the growth drivers that I discussed in my prior article about the impact of COVID on network infrastructure, these additional applications intensify the need for edge infrastructure that brings computing far closer to where end users need it.

About the Author

Keith Rutledge is the General Manager of Compass EdgePoint, which provides zero-touch edge datacenter solution at scale for a wide range of customers. Compass EdgePoint is part of Compass Datacenters, which provides custom, move-in ready data centers from edge deployments to core facilities serving hyperscale, cloud and enterprise customers. In a long career at IBM prior to this leadership role at Compass EdgePoint, Rutledge was a printed circuit board designer, a software developer, a product manager, and a sales executive. As a product manager, Keith wrote The Business Case for Java and edited The Business Case for eBusiness – which served as strategic touchstones for IBM’s business strategy. He ran Central Europe Middle East and Africa for IBM’s AS/400 product and was Worldwide Director of Sales for the AS/400. Keith also led a strategic outsourcing practice in China for IBM. Prior to IBM, Rutledge worked at Sirius, where he was responsible for partners and routes to market before becoming Director of Sales and General Manager for Sirius Southeast. He also had a long military career in Special Forces, retiring in 1999 as a Team Sergeant from 19^th Special Forces Group.

 

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Categories: Datacenter · Industry Viewpoint