Edge computing solutions address a number of issues emerging as enterprise IT organizations deploy more Internet-connected devices – and seek to make use of the volumes of valuable data produced far from centralized networks or public clouds. Indeed, enterprises may spend an average of 30 percent of their IT budgets on edge cloud computing over the next three years, according to Analysys Mason.
“To remain competitive in the post-cloud era, innovative companies are adopting edge computing due to its endless breakthrough capabilities that are not available at the core,” says David Williams, managing principal at AHEAD. “Such benefits include unparalleled local interactivity, reduced impact from service interruptions, improved privacy and security, and reduced latency.”
As Dave McCarthy, a research director within IDC’s worldwide infrastructure practice who focuses on edge strategies, told the Enterprisers Project for our look at edge computing trends to watch in 2020, most enterprises underestimated the volume of data that Internet of Things (IoT) devices can generate and how hard it is to separate out the most important data.
What problems does edge computing solve?
The cost of transmitting and storing all of that data without a clear benefit led many to wonder whether IoT was worth the hype. “That is why the industry is pivoting to edge computing,” McCarthy says. “By processing data closer to the point of generation, it is possible to avoid unnecessary communication and storage costs while simultaneously applying machine learning and AI to identify data patterns that have an impact to the business.”
[ Want to learn more about implementing edge computing? Read the blog: How to implement edge infrastructure in a maintainable and scalable way. ]
Organizations across industries can expect a 10 to 30 percent reduction in costs from using edge computing and an average operational cost-saving of 10 to 20 percent, according to Analysys Mason. But lower costs tell just part of the story. Gartner predicts that by 2025, three-quarters of enterprise-generated data will be created and processed at the edge.
Here are some of the key problems that edge computing can address:
1. Enterprise IT problem: Many industrial IoT solutions demand total uptime
This is particularly true for those designed to improve worker safety or asset management. These solutions that rely on internet connectivity are untenable since outages could, for example, halt production in a factory or make a work zone dangerous, according to Aaron Allsbrook, CTO of edge computing software maker ClearBlade.
Edge solution: Enterprises in the construction, manufacturing, mining, and oil and gas industries, for example, are embracing the edge, which enables them to run the core elements of any solution locally by empowering local devices to save their state, interact with each other, and send important alerts and notifications. “This means that even if the internet goes down the factory, warehouse, construction site, mine, or field, edge processing continues to work full steam ahead,” Allsbrook says.
Use case example: Use cases in the construction industry center around managing projects, ensuring worker safety, and increasing productivity. “Machinery in hazardous environments could be operated remotely by using low-latency edge computing to avoid endangering a construction worker,” Dalia Adib, practice lead for edge computing at research and consulting firm STL Partners, wrote in IoT World Today. “Another use case for health and safety is being able to monitor the environment and pollution to create real-time alerts if they breach a safety threshold.”
[ Get a shareable primer: How to explain edge computing in plain English.]
2. Enterprise IT problem: IoT solutions can require an expensive network
Enterprises may find that a pricey network comes along with the number of devices needed to provide information of value to the organization.
Edge solution: Edge computing can minimize the network and bandwidth issues associated with moving large amounts of data to or from IoT devices and reduce reliance on the network. Companies look to edge solutions that can process data at the source and provide summary information on what’s going on. This eliminates the need for expensive SIM cards, data plans, and other network costs if the data were to have to be transported from the device to a network. “Edges can use simple ‘if-then’ logic or advanced AI algorithms to understand and build those summary reports,” explains Allsbrook of ClearBlade.
Use case example: Some passenger and freight railroad operators are embracing the edge to help them create a smart IoT platform to digitize their extensive and sometimes aging infrastructure. Specifically, they are deploying an IoT-edge combo to increase safety at railroad crossings and reduce the associated maintenance costs. With edge processing, they can reduce the volume of data about the health of the gates, bells, signals, and batteries at crossings to simple failure messages which, Allsbrook says, they can send over low-cost LoRa (long-range radio) peer-to-peer networks and then cheaply backhaul home in small payloads.
3. Enterprise IT problem: Consumer IoT applications demand real-time processing of localized events
This real-time processing helps provide value in operational decision-making and customer targeting and personalization.
Edge solution: In a retail environment, for example, beacons can collect information on customers. Edge processing can be deployed to send shoppers targeted promotions and sales items as customers walk through the store. Companies may also move operational applications to the edge to enhance real-time decision making.
Use case example: One nationwide café-style restaurant chain was experiencing disruptions at the core, resulting in restaurant wide – and sometimes nationwide – outages, hindering real-time engagement with customers and wasting precious capital, according to Williams of AHEAD.
Moving café operations applications to the edge completely transformed the way the restaurant develops, delivers, and runs its applications, enabling it to better manage its more than 2000 locations in real-time restaurants, maximize daily profitability, and enhance customer and employee experience. “Furthermore, by adopting edge computing, the company gained greater control over café operations via actionable data and localized events, allowing café-independent campaigns to be managed and operated at the café level,” says Williams. “This, in turn, improved the autonomy for local operations, empowering individual cafés to make adjustments as needed in real-time.”
4. Enterprise IT problem: Connecting aging legacy devices in the field that communicate using older machine protocols
Edge solution: Mobile edge computing devices can be used to capture data from sensors attached to legacy equipment. Organizations are using edge computing capabilities to translate out-of-date machine protocols into more modern languages and compute a variety of data coming in from different sensors to, say, provide the machine with accurate operational information or produce intelligence that can be used for other purposes.
Use case example: Buildings with older building management, security, or security systems can use edge solutions to improve their operations, says ClearBlade’s Allsbrook. They are looking at deploying edge-based people-counting, using data provided by security systems and cameras, for example, to turn on cooling systems or alerting customer representatives that a client has arrived on site.
[ Why does edge computing matter to IT leaders – and what's next? Learn more about Red Hat's point of view. ]
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