Learn about the key concepts of the edge, why it’s useful to developers, and where to get started.
Many companies want Internet of Things (IoT) devices to monitor and report on events at remote sites, and this data processing must be done remotely. The term for this remote data collection and analysis is edge computing.
Edge computing technology is applied to smartphones, tablets, sensor-generated input, robotics, automated machines on manufacturing floors and distributed analytics servers that are used for “on the spot” computing and analytics.
Read this cheat sheet to learn more about edge computing. We’ll update this resource periodically with the latest information about edge computing.
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Edge computing refers to computing resources, such as servers, storage, software and network connections, that are deployed at the edges of the enterprise. For most organizations, this requires a decentralization of computing resources, so some of these resources are moved away from central data centers and directly into remote facilities such as offices, retail outlets, clinics and factories.
Some IT professionals might argue that edge computing is not that different from traditional distributed computing, which saw computing power move out of the data center and into business departments and offices several decades ago.
SEE: IT leader’s guide to edge computing (TechRepublic Premium)
However, edge computing is different because of the way edge computing is tethered to IoT data collected from remote sensors, smartphones, tablets and machines. This data must be analyzed and reported on in real time, so its outcomes are immediately actionable for personnel at the site.
IT departments in virtually every industry use edge computing to monitor network security and to report on malware and/or viruses. When a breach is detected at the edge, it can be quarantined, thereby preventing a compromise of the entire enterprise network.
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It is projected that by 2020 there will be 5.6 billion smart sensors and other IoT devices employed around the world. These smart IoT devices will generate over 507.5 zettabytes (1 zettabyte = 1 trillion gigabytes) of data.
By 2023, the global IoT market is expected to top $724.2 billion. The accumulation of IoT data and the need to process it at local collection points is what’s driving edge computing.
Businesses will want to use this data. The catch is the data that IoT generates will come from sensors, smartphones, machines and other smart devices that are located at enterprise edge points that are far from corporate headquarters.
This IoT data can’t just be sent into a central processor in the corporate data center as it is generated because the volume of data that would have to move from all of these edge locations into HQs would overwhelm the bandwidth and service levels that are likely to be available over public internet or even private networks.
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As organizations move their IT to the “edges” of the organization where the IoT devices are collecting data, they are also implementing local edge commuting that can process this data on the spot without having to transport it to the corporate data center.
This IoT data is used for operational analytics at remote facilities. The data enables local line managers and technicians to immediately act on the information they are getting.
Companies need to find ways to utilize IoT that pay off strategically and operationally. The greatest promise that IoT brings is in the operational area, where machine automation and auto alerts can foretell issues with networks, equipment and infrastructure before they develop into full-blown disasters.
For instance, a tram operator in a large urban area could ascertain when a section of track will begin to fail and dispatch a maintenance crew to replace that section before it becomes problematic. Then, the tram operator could notify customers via their mobile devices about the situation and suggest alternate routes, and great customer service helps boost revenues.
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70% of Fortune 100 companies already use IoT edge technology in their business operations. With an IoT market that is expected to grow at a compound annual growth rate (CAGR) of 14.8% through 2027, major IT vendors are busy promoting edge computing solutions because they want their corporate customers to adopt them. These vendors are purveying edge solutions that encompass servers, storage, networking, bandwidth, and IoT devices.
SEE: Special report: Sensor’d enterprise: IoT, ML, and big data (free PDF) (TechRepublic)
Affordable cloud-based solutions for edge computing also enable companies of all sizes to move computers and storage to the edges of the enterprise.
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Edge computing affects companies of all sizes in virtually every public and private industry sector.
Projects can be as modest as placing automated security monitoring on your entryways to monitoring vehicle fleets in motion, controlling robotics during telesurgery procedures, or automating factories and collecting data on the quality of goods being manufactured as they pass through various manufacturing operations half a globe away.
One driving factor for edge computing is the focus on IoT by commercial software vendors, which are increasingly providing modules and capabilities in their software that exploit IoT data. Subscribing to these new capabilities doesn’t necessarily mean that a company has to invest in major hardware, software and networks, since so many of these resources are now available in the cloud and can be scalable from a price point perspective.
Companies that do not take advantage of the insights and actionability that IoT and edge computing can offer will likely be at a competitive disadvantage in the not so distant future.
An example is a tram operator in a large urban area that uses edge IoT to ascertain when a section of track will begin to fail and then dispatches a maintenance crew to replace that section of track before it becomes problematic. At the same time, it notifies customers in advance that the track will be worked on and offers alternate routes.
What if you operated a tram system, and you didn’t have advanced IoT insights into the condition of your tracks or the ability to send messages to customers that advised them of alternate routes? You would be at a competitive disadvantage.
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IoT and edge computing are used in a broad cross-section of industries. Within these organizations, executives, business leaders, and production managers are some of the people who will rely on and benefit from edge computing.
Here are some common use cases that illustrate how various industries are using edge computing:
IoT and edge computing is also being used by:
Businesses can implement edge computing either on-premises as a physical distribution of servers and data collection devices or through cloud-based solutions. Intel, IBM, Nokia, Motorola, General Electric, Cisco, Microsoft and many other tech vendors offer solutions that can fit on-premise and cloud-based scenarios.
There are also vendors that specialize in the edge computing needs of particular industry verticals and IT applications, such as edge network security, logistics tracking and monitoring, and manufacturing automation. These vendors offer hardware, software and networks as well as consulting advice on how to manage and execute an edge computing strategy.
SEE: Free ebook—Digital transformation: A CXO’s guide (TechRepublic)
To enable a smooth flow of IoT generated information throughout the enterprise, IT needs to devise a communications architecture that can facilitate the real-time capture and actionability of IoT information at the edges of the enterprise as well as figure out how to transfer this information from enterprise edges to central computing banks in the corporate data center.
Companies want as many people as possible throughout the organization to get the information so they can act on it in strategically and operationally meaningful ways.
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Edge computing moves some of the data processing and storage burdens out from the central data center and spreads them to remote processors and storage that reside where the incoming data is captured.
By moving processing and storage to remote sites at the age of the enterprise, those working and managing at these sites can obtain immediate analytics from incoming IoT data that can aid them in doing and managing their work.
When companies process data at remote sites, they save on the data communications and transport costs that would be incurred if they had to ship all of that data to a central data center.
There are a host of edge computing tools and resources available in the commercial marketplace that can screen and secure data, quarantine and isolate it if needed, and immediately prepare and process it into analytics results.
For IT, edge computing is not a slam-dunk proposition. It presents significant challenges, which include:
Mary E. Shacklett is president of Transworld Data, a technology research and market development firm. Prior to founding the company, Mary was Senior Vice President of Marketing and Technology at TCCU, Inc., a financial services firm; Vice President of Product Research and Software Development for Summit Information Systems, a computer software company; and Vice President of Strategic Planning and Technology at FSI International, a multinational manufacturing company in the semiconductor industry. Mary is a keynote speaker and has more than 1,000 articles, research studies, and technology publications in print.
