Edge Computing, or the “intelligent edge” has become almost a buzzword in today’s IoT industry discourse. There are so many “platforms” in IoT that it’s become hard for even experts to keep them straight. But what is an Edge Platform?
Perhaps it would be useful to level-set first by defining the Edge itself. Edge Computing brings processing capabilities as close as possible to the device that actually generates and/or uses the data that makes a process happen. It lives on the physical computing infrastructure at the point of operation, usually, and often is designed to work in tandem with cloud or remote server computing in well-orchestrated systems and to be the most effective at performing IoT operations.
Edge computing enables secure data processing at the edge of the network – making data instantly available to users with low latency and reliable access. Since 75 percent of enterprise data is created at remote sites, like branch offices, manufacturing plants, mobile devices and on IoT-enabled smart devices, more enterprises are looking to deploy computing power at the network edge.
Edge computing is important for a number of reasons. One is improved response time that comes from local processing of data so information doesn’t have to travel as far as it would under a traditional cloud deployment, making it available sooner.
Edge computing also supports constant availability of applications, even during connectivity or cloud outages. Edge data centers are positioned close to end users, reducing the likelihood of a network problem affecting local customers. Intelligent edge systems also improve security and privacy by reducing the need to send sensitive information to the cloud. Processing at the edge distributes the storage, load, and use of applications across types of devices and data centers, making it less likely for a disruption to shut down the network.
Major enterprise and IIoT companies are already using the edge, including military and first responder units that are seeking to leverage real-time actionable information and deploy autonomous vehicles and drone systems. This Internet of Military Things (IOMT) is one among many industries in urgent need of applications that can only be powered by edge computing.
In the context of Industry 4.0 or IIoT, edge computing is already beginning to enable augmented reality, decision-making AI, and machine learning. The key element for the growth of AI and M2M is a strong edge architecture that uses biometrics, environmental sensors, and other connected devices to send and receive data quickly. The edge is foundational to these changes that are just on the horizon.
EDJX is building for Industry 4.0 and the Fourth Internet which is predicted to encompass more than a trillion connected devices, and the cloud won’t be able to keep up. Data processing needs to be closer to where data is being generated.
The reasons for deploying Edge Computing are simple to understand. Edge computing brings storage and computing closer to end users (people or machines), which lowers latency, speeds up operations, and makes the entire network more responsive and resilient.
A well-designed edge platform would significantly outperform a traditional cloud-based system. Some applications rely on short response times, making edge computing a significantly more feasible option than cloud computing. Examples range from IoT to autonomous driving, sensor data fusion applications, public safety applications, and technologies such as facial recognition, which typically takes a human between 370-620 ms to perform. Edge computing-enabled applications are more likely to be able to mimic the same perception speed as humans, which is useful in cases such as augmented reality where the headset should preferably recognize who a person is, at the same time as the wearer does. The decentralized architecture inherent to edge computing also serves to decrease the bandwidth needed to run an IoT system, as data processing occurs near the point of collection. Only the necessary data, collated results of analysis, or actuating data need be transferred, so Edge Computing can also drive savings in network spend via reducing network load, as well as manifold other efficiencies which speed the scalability of IoT applications.
So What’s an Edge Platform, then?
An edge platform de-tethers applications and enterprises from the hub-and-spoke cloud network topology, organizing a distributed edge network, which allows systems to take advantage of the benefits of the Edge as discussed above. The lowered latency from closer proximity to the raw data and on-device processing helps the user to act faster upon critical data as it is identified.
Basically, though, an Edge Platform is a software environment, housed upon multiple hardware devices in the network, and that software is used to both run applications, and speed action upon new information.
Edge computing platforms enable the edge network architecture to scale while still processing and acting upon data locally.
What’s the market for Edge Platforms?
Predictions for the Edge market vary wildly (of course), but most firms are looking at an overall edge market in the neighborhood of $170 billion this year, and that means that Edge Platforms are becoming ever more necessary to manage that growth.
Many networking companies of all sizes, from behemoth to start-up are entering the Edge Platform market, as both providers and customers, trying to help partners bring their processing and data operations closer to the Edge, at scale.
A quality edge computing platform needs to ensure ultra-low latency and high performance computing. Such a platform doesn’t sacrifice high-performance computing, powerful storage, or network resources while placing them as close as possible to the edge of the network where the assets are needed. They also work in tandem with cloud or other remote storage and processing solutions.
There are many options for deploying edge computing, but if you want to scale, you’re going to have to leverage a platform to manage all the operations, data, and devices you need to deploy throughout the edge of your network.
It doesn’t matter if you’re already using the edge or just getting into it -- now is the time to consider an edge platform solution.
About the author: Laura Roman PhD is CMO at EDJX. In this role, she works with the EDJX team to ensure the impact and authenticity of EDJX’s brand, leads demand gen, digital marketing, GTM enablement, product marketing, AR/PR, corporate and internal communications and culture. Prior to EDJX, Laura was Vice President, VC and Emerging Technologies at Sparkpr and before that, held senior positions at HP, Cisco, Cision, Groupon, and Vmware. In her broader background Laura was a Stanford Lecturer, Oxford University Research Fellow and also holds a PhD in English from Oxford University.
Be part of the conversation at Intelligent Edge Expo 2022, taking place June 21-24, 2022 in Ft. Lauderdale, Florida as part of IoT Evolution Expo and #TECHSUPERSHOW. Intelligent Edge Expo will focus on the Intelligent edge as its own entity and as part of the larger Systems of Systems that is the Internet of Things of today and the future, and the sensors, gateways, endpoints, network connections that comprise the Intellgence Edge and help IoT-enabled organizations become ever more efficient, sustainable and profitable.
Edited by Erik Linask