Edge computing is the practice of placing computing, data storage and application resources closer to data sources (like IoT devices or local databases and servers). Reducing the physical proximity between these entities reduces data latency and speeds up overall network performance.
Edge Computing Definition
Edge computing is a distributed computing framework that brings computing and data storage closer to devices, reducing the amount of data needed to move around and making responses faster.
“The whole point of edge computing is to get closer to devices, to reduce the amount of data that needs to be moved around for latency reasons, to get closer so that responses are faster,” said Matt Trifiro, chief marketing officer at Vapor IO.
Edge Computing Basics
The basic idea of edge computing is this: A data job that requires little or no travel typically can be completed more quickly and easily than one that requires a long trek — especially if, at the end of said journey, lots of other workers need to use your machine.
These days, there’s a good chance that everything from the light bulb in your kitchen to the car in your garage is “connected.” That never-ending — and always-increasing — stream of data processing jobs means heavy strain on data centers. Edge computing eases that burden by moving some of the processing closer to its point of origin — as close as possible to where the action occurs.
And so, rather than traveling to the cloud, the data processing is done “on the edge.” Sometimes that means the processing occurs where it’s launched — in the device itself. Think sensor-equipped wind turbines and assembly machines. For bigger jobs, it also sometimes means processing in “cloudlets,” which are essentially decentralized mini-data centers that can handle certain commands of certain users.
Some industry watchers believe the cloud will one day be used mostly for storage and massive computations. And due to the massive amounts of data they gobble up, many of tech’s future marquee breakthroughs — things like self-driving cars that rely on LIDAR to avoid crashes and large-scale drone delivery — are almost certain to incorporate edge data centers. Major innovations that are now taking off, like IoT, AI and high-tech farming also lean on the edge.
How Does Edge Computing Work?
With edge computing, the main goal is to process data at the exact location, or as close as possible, to where it’s being created and used. To accomplish this, data is processed right outside of a core network (which encompasses the internet and IP technologies) at the network edge, the area where devices and local servers connect to and communicate with the internet.
The devices that process data on the network edge are called edge devices. Edge devices help collect and filter data on-device or through local edge servers and transmit only the most necessary data to data centers situated atop the core network (like the cloud and data warehouses). These edge devices can include motion sensors, smart cameras, smart thermometers, robots, drones and other IoT sensors.
Why Is Edge Computing Important?
By processing data on a network’s edge, unnecessary data is removed early on, which means you don’t have to send data all the way between devices and the cloud for processing. This in turn reduces transmission times and costs, as well as increases processing capabilities at remote locations. And, with less data being transmitted between networks, and with data stored on close-proximity edge devices versus personal devices, security threats are prevented.
Benefits of Edge Computing
Faster Response Times
Low data latency, less data traffic and spending less time transmitting data between networks means quicker response times on software applications. This can help alert workers of machinery errors immediately or help self-driving cars identify obstacles more quickly.
Lowered Cloud and IT Costs
Not all data collected by edge sensors is sent to data centers, which reduces data management needs, transmission costs and costs needed to process and store data in the cloud.
Increased Security and Privacy
By using edge computing, data can be stored and travel between different encrypted edge devices, servers and gateways. This forms a decentralized data infrastructure where data isn’t stored all in one place, as opposed to the centralized infrastructure used in the cloud.
Edge computing’s decentralized nature means one compromised edge device doesn’t affect data on all other devices. Extra security measures can also be implemented directly on edge devices like firewalls or intrusion detection systems.
Challenges With Edge Computing
Complicated to Set Up
In addition to what some view as insufficient cooperation between hardware builders and software providers, the fact remains that building out an edge computing network is difficult work. For example, Vapor IO had to figure out how to make its modules operate in some remote hinterlands while also supporting multiple tenants, giving clients the ability to remotely observe processing speeds, and keeping the whole operation humming without need for constant on-site maintenance.
Hardware Constraints
As advanced as digital tech gets, hardware stubbornly remains beholden to physical conditions. Examples include the fan in your laptop or complex chilled water or oil systems in large-scale data centers. To that end, Vapor IO designed its server racks as cylinders rather than rectangles in order to optimize airflow. It also added a host of sensors, monitors and air redirects to maintain ideal temperatures.
Physical Security Vulnerabilities
As a network is pushed further from the fortress-like cloud, issues arise regarding the physical security of outposts — even as the edge makes data transmission more secure. But that might be less liability than opportunity.
Development of tamper-resistant hardware and tamper-prompted data erasure stalled out a bit as cloud computing took off in the early 2000s, but the rise of edge computing will likely resuscitate both research and business opportunities in the field, said Mahadev “Satya” Satyanarayanan, computer science professor at Carnegie Mellon University.
“As edge computing becomes prominent and important, many of these [security] ideas that have kind of been dormant will become significant again,” Satyanarayanan said. “You might see lines of edge-deployable hardware that have some additional hardening.”
Elemental Vulnerabilities
Edge data centers must also be able to withstand external elements. As the authors of a report by edge membership organization State of the Edge wrote, “Unlike centralized hyper-scale data centers, which can be carefully and methodically located, edge data centers often need to go near the data, no matter how harsh the location.” Flood and seismic risks, air pollution and temperature fluctuation all must be taken into consideration.
Requires Specific Land and Materials
Access to land and fiber can be hurdles, too. Crown Capital — a partner of Vapor IO and the largest owner of wireless infrastructure in the United States — has a lot of both, including in Chicago, Illinois, where its expansive fiber routes connect Vapor IO’s edge modules. The city has long been America’s railway hub. After railroad companies used their land-grant rights to have telco partners run fiber-optic lines along rail lines, it also became a major fiber hub. Network-wise, not all cities are so fortunate.
Access to power sometimes poses a challenge, as well. Take the aforementioned Chicago structure where Vapor IO set up a rack chamber: it already existed as a Crown Capital site, which meant plenty of juice was already flowing through it. Similar sites, attractive though they may be, aren’t always so lucky. Vapor IO sometimes has to wait months for an electric company or utility to extend the necessary power lines.
All of which is to say, the edge industry needs copious capital to flourish. According to Trifiro, the deployment of data centers requires “multiple millions of dollars per city.”
While the advancement of edge computing is rife with challenges, none appears to be anything resembling an existential threat — especially considering the imminent tsunami of forthcoming technology.
Applications of Edge Computing
Autonomous Vehicles
Edge computing can help autonomous vehicles and self-driving cars process data around them at faster speeds, all without the need for the cloud. This could increase vehicle reaction times and reduce accidents, as well as keep vehicle operations up when offline or in a rural area, making for safer travel.
Banking and Finance
The security features of edge computing can help make banking and financial services more secure. ATMs using biometric authentication can process facial or fingerprint data in real time and immediately alert authorities if fraud is detected. Plus, since user data would be stored locally with edge devices, this prevents possible data loss from having to transfer banking data to data centers.
Gaming
Low data latency in edge computing translates to less lag and faster load speeds, meaning less interruptions while gaming. AI characters and interactivity for online games could also be enhanced, as data would be processed locally and in real time to match a player’s capabilities.
Healthcare
In healthcare, equipment and wearables using edge computing can give professionals an almost instant look at patient vitals like blood pressure, heart rate and oxygen levels. Combining edge and AI technology may also detect anomalies more quickly in medical images and highlight immediate health concerns.
Smart Homes
Smart homes rely on various IoT sensors to function, tracking aspects like motion, air, moisture and temperature. Utilizing edge computing for these devices ensures everything in a home is operating based on instant analytics, allowing the home to automatically adjust temperatures or quickly alert residents of carbon monoxide detection.
Will Edge Computing Take Off?
Despite an ever-increasing number of computing devices and key early-stage gains by edge companies, Satyanarayanan said edge computing is still in a holding pattern.
It’s difficult to kickstart — particularly in terms of supply chain.
“You need network operators, cloud providers, equipment providers, middleware orchestration applications, software providers,” Trifiro said. “You need that whole value chain.”
Developers of edge-dependent applications may also be more incentivized to ramp things up if they were confident that infrastructure builders were investing big in the edge, Satyanarayanan explained. But edge computing creators likewise want to see that same demonstrable commitment from developers.
One potential way to resolve the standoff and ignite the necessary partnership? A successful bridge application, one that — to borrow a product phrase — crosses the chasm, moving from early adopters to the broader public.
But some builders are hardly idle while we await edge computing’s breakthrough moment. Even if there aren’t many major edge examples to bounce off of, the technology’s already being recognized by big players like Microsoft, IBM and Intel, meaning opportunities for developers to jump into edge computing may only grow.
