What Is Edge Computing?

This remains a proven and time-tested approach to client-server computing for most typical business applications. Analytics need to be located close to the edge for applications where near-real-time feedback and optimization are a priority – such as autonomous vehicles and machine-to-machine applications. After all, we don’t want an internet traffic jam to result in a real-life accident.

Or your edge may be colocation data centers, managed hosting providers, or private cloud hosting providers that bring your application within one to 50 miles of thousands of consumers. Intel’s experience developing solutions that bridge data storage, transmission, processing, and analysis has resulted in tens of thousands of edge deployments powered by Intel. For an enterprise that doesn’t have much trouble dispatching a fleet of trucks or maintenance vehicles to field locations, micro data centers (µDC) are designed for maximum accessibility, modularity, and a reasonable degree of portability.

But the other reason this feels like edge computing to me, not personal computing, is because while the compute work is distributed, the definition of the compute work is managed centrally. You didn’t have to cobble together the hardware, software, and security best practices to keep your iPhone secure. You just paid $999 at the cellphone store what is edge computing in simple terms and trained it to recognize your face. Edge computing is computing that’s done at or near the source of the data, instead of relying on the cloud at one of a dozen data centers to do all the work. The concept dates back to the 1990s, when Akamai solved the challenge of Web traffic congestion by introducing Content Delivery Network solutions.

How Do Companies Use Edge Computing With Datacenters And Public Cloud?

The former relies on a central computing model that delivers services, processes and data services, while the latter refers to a computing model that’s highly distributed. First, it must take into account the heterogeneity of the devices, having different performance and energy constraints, the highly dynamic condition, and the reliability of the connections compared to more robust infrastructure of cloud data centers. Moreover, security requirements may introduce further latency in the communication between nodes, which may slow down the scaling process. By drawing computation capabilities in close proximity of fleet vehicles, vendors can reduce the impact of communication dead zones as the data will not be required to send all the way back to centralized cloud data centers.

If you’ve read or heard elsewhere that the edge could eventually subsume the whole cloud, you may understand now this wouldn’t actually make much sense. Connect with the leading IT Infrastructure and operations (I&O) leaders to get the latest insights needed to take https://globalcloudteam.com/ your strategy to the next level. Red Hat Enterprise Linux provides a large ecosystem of tools, applications, frameworks, and libraries for building and running applications and containers. Physical security of edge sites is often much lower than that of core sites.

TierPoint’s data center fabric provides any-to-any high-speed connectivity. Fast, flexible interconnectivity enables the use of other advanced networking technologies and the delivery of managed services, such as disaster recovery. You’ll find everything you need to know about edge computing, how it works with cloud computing, the impact of 5G, and how to look for best-in-class edge data centers.

By one estimate, a modern plant with 2,000 pieces of equipment can generate 2,200 terabytes of data a month. It’s faster—and less costly—to process that trove of data close to the equipment, rather than transmit it to a remote datacenter first. But it’s still desirable for the equipment to be linked through a centralized data platform. That way, for example, equipment can receive standardized software updates and share filtered data that can help improve operations in other factory locations.

Countless billions of dollars have been thrown into making driverless vehicles along with other improvements through edge computing solutions in the automotive industry. These vehicles will need to gather and process massive quantities of data in real-time to remain safe and effective, such as weather, road conditions, and potential hazards. For that reason, keeping this data stored or accessible as close as possible to major avenues of travel will make these operations significantly more streamlined and efficient. Edge computing is relevant far beyond just simple data collection for B2B enterprises. There are a number of examples of edge computing beyond what you might think of, and some you already did.

Gartner estimates that by 2025, 75% of data will be created and processed outside the traditional data center or cloud. But cars also represent a full shift away from user responsibility for the software they run on their devices. The management aspect of edge computing is hugely important for security.

The first vital element of any successful technology deployment is the creation of a meaningful business andtechnical edge strategy. Understanding the “why” demands a clear understanding of the technical and business problems that the organization is trying to solve, such as overcoming network constraints and observing data sovereignty. Edge computing addresses vital infrastructure challenges — such as bandwidth limitations, excess latency and network congestion — but there are several potentialadditional benefits to edge computingthat can make the approach appealing in other situations. Latency.Latency is the time needed to send data between two points on a network.

Processed data, like oil from a refinery, is pumped back out toward the edge for delivery. CDNs expedite this process by acting as “filling stations” for users in their vicinity. The typical product lifecycle for network services involves this “round-trip” process, where data is effectively mined, shipped, refined, and shipped again.

How Does Edge Computing Work & What Are The Benefits?

At this stage in the game, the world will require advanced computing solutions to save our finite resources and prevent climate change. Here are some of the most life-changing edge computing use cases we think will take over the tech world this decade. This is computing “at the edge.” The edge being real-time, where people and machines use the information to make decisions quickly. While server farms and data warehouses were once thought to be the final solution for speed and capacity, the pendulum is swinging back to an old-school-esque network of devices. Controlover the space, to ensure only authorized personnel have access to edge infrastructure.

While these hurdles are not insurmountable, organizations should consider them before embarking on an edge computing initiative. In any telecommunications network, the edge is the furthest reach of its facilities and services towards its customers. In the context of edge computing, the edge is the location on the planet where servers may deliver functionality to customers most expediently.

Examples include smart buildings, smart cities or even smart utility grids. Consider a smart city where data can be used to track, analyze and optimize the public transit system, municipal utilities, city services and guide long-term urban planning. A single edge deployment simply isn’t enough to handle such a load, so fog computing can operate a series offog node deploymentswithin the scope of the environment to collect, process and analyze data.

Deploying Edge Data Centers

Ensure edge sites continue to operate in the event of network failures. Address the needs of different edge tiers that have different requirements, including the size of the hardware footprint, challenging environments, and cost. But the big picture is that the companies who do it the best will control even more of your life experiences than they do right now. Then, in the Unix era, we learned how to connect to that computer using dumb terminals. Next we had personal computers, which was the first time regular people really owned the hardware that did the work.

Servers capable of providing cloud-like remote services to commercial customers, regardless of where they’re located, need high-power processors and in-memory data, to enable multi-tenancy. Probably without exception, they’ll require access to high-voltage, three-phase electricity. That’s extremely difficult, if not impossible, to attain in relatively remote, rural locations. (Ordinary 120V AC current is single-phase.) Telco base stations have never required this level of power up to now, and if they’re never intended to be leveraged for multi-tenant commercial use, then they may never need three-phase power anyway.

• This big step in network infrastructure enabled IoT devices and services to move closer to the end-user.
• Real-time, high-bandwidth, low-latency access to latency-dependent applications, distributed at the edge of the network.
• The alternative – a series of ad hoc IT deployments – creates a nightmare scenario for both speed of deployment and ongoing management.
• By moving data processing at or near the source of data generation, edge devices become smarter and they’re able to handle tasks that would have been unimaginable only a few years ago.

Ask your vendor about extended services that maximize intelligence and performance at the edge. CIOs in banking, mining, retail, or just about any other industry, are building strategies designed to personalize customer experiences, generate faster insights and actions, and maintain continuous operations. This can be achieved by adopting a massively decentralized computing architecture, otherwise known as edge computing. Within each industry, however, are particular uses cases that drive the need for edge IT. The explosive growth and increasing computing power of IoT devices has resulted in unprecedented volumes of data.

“But what we’re seeing, with all the different changes in usage based on consumer behavior, and with COVID-19 and working from home, is a new and deeper edge that’s becoming more relevant with service providers.” Ideally, perhaps after a decade or so of evolution, edge computing would bring fast services to customers as close as their nearest wireless base stations. We’d need massive fiber optic pipes to supply the necessary backhaul, but the revenue from edge computing services could conceivably fund their construction, enabling it to pay for itself. For telcos, the apps and services their customers want to consume on edge networks are the key to revenue generation, but success depends on building the right ecosystem and coordinating among stakeholders and technology partners alike. 5G refers to the fifth generation of mobile networks, representing upgrades in bandwidth and latency that enable services that weren’t possible under older networks. 5G networks promise gigabit speeds—or data transmission speeds of up to 10 Gbps.

A Brief History Of Edge Computing

These systems can provide real-time assessments of energy usage and note any irregularities, as well as maximize energy efficiency of energy sources like wind and solar. Improving the customer experienceCustomers see examples of IoT applications all around them. Digital signage improves their retail shopping and transportation experiences. Industrial field service personnel use augmented reality applications to help them more easily service complicated machines and devices. You can now do most of your banking from your phone and have your healthcare devices monitored from afar.

Network speeds are reliable most of the time, but “most of the time” isn’t good enough for things like autonomous driving, medical devices, and natural disaster response tools. Since the mainframe computer in the 1970s, computing power has grown exponentially, doubling processing power while halving costs every year. Now that we’ve established the differences between the computing models, we can now look at how edge computing is being implemented today. With a global career in IT Channels Strategy, Sales Operations and Offer Management, Jamie brings a unique set of competencies needed in evaluating and delivering on the current disruptions in the market. White Paper 277 highlights the benefits of an integrated ecosystem of tools, partners, and solutions for edge computing.

Intel® Edge Computing Technology And Solutions

For users, edge computing means a faster, more consistent experience. For enterprises and service providers, edge means low-latency, highly available apps with real-time monitoring. A step further is autonomous vehicles—another example of edge computing that involves processing a large amount of real-time data in a situation where connectivity may be inconsistent. Because of the sheer amount of data, autonomous vehicles like self-driving cars process sensor data on board the vehicle in order to reduce latency.

How Edge Relates To Cloud Computing

An infrastructure and application development platform that is flexible, adaptable, and elastic is required to fulfill these different needs and provide the connection between these various stages. Your Red Hat account gives you access to your member profile, preferences, and other services depending on your customer status. An edge framework introduces flexibility, agility and scalability that’s required for a growing array of business use cases. For example, a sensor might provide real-time updates about the temperature a vaccine is stored at and whether it has been kept at a required temperature throughout transport.

For example, 5G provides a high-bandwidth, low-latency connection for rapid data transfer and service delivery from the edge. But it doesn’t make financial sense to do all your data processing and storage in the cloud—and it might not be feasible for security or compliance reasons as well. A solid edge computing strategy is often a necessary balance for a good cloud computing strategy. The most important part of edge technology is that it’s a form of distributed computing.

Indeed, improving operational efficiency is probably the biggest single reason companies deploy IoT applications. Many IoT applications rely on cloud-based resources for compute power, data storage and application intelligence that yields business insights. However, it’s often not optimal to send all the data generated by sensors and devices directly to the cloud, for reasons that generally come down to bandwidth, latency and regulatory requirements. The IoT involves collecting data from various sensors and devices and applying algorithms to the data to glean insights that deliver business benefits.

Despite the improvements of network technology, data centers cannot guarantee acceptable transfer rates and response times, which, however, often is a critical requirement for many applications. Furthermore, devices at the edge constantly consume data coming from the cloud, forcing companies to decentralize data storage and service provisioning, leveraging physical proximity to the end user. Sending all that device-generated data to a centralized data center or to the cloud causes bandwidth and latency issues. Edge computing offers a more efficient alternative; data is processed and analyzed closer to the point where it’s created. Because data does not traverse over a network to a cloud or data center to be processed, latency is significantly reduced.