What is an edge network?

Edge networks are so named because that’s where their data processing power and apps are concentrated—at the edge of networks. That geographical change is key because by relocating these workflows to the network edge, an organization can realize faster operation and safer performance.

Edge networks contribute to the overall field of edge computing, which is a distributed computing framework that brings enterprise applications closer to the point where data is created and actions are being taken. Edge computing helps organizations limit latency while boosting network speeds, bandwidth and reliability. This results in faster and more comprehensive data analysis, deeper insights, quicker response times and improved individual experiences. Edge computing can absorb data created and transmitted by nearby endpoint edge devices, then utilize a machine learning program to perform data analysis and glean practical guidance, based on such analysis.

Service providers offer various solutions to fit the computing needs of particular companies. An edge-network strategy represents a different computing paradigm (or approach) in that it seeks not to move processing toward data storage facilities, but to move asset functionality away from data centers and to the edge devices connected through this network.

Before proceeding, it’s important to spell out what we mean by “edge devices.” The term is essential to any understanding of edge networks but must be viewed within the specific context used because the phrase encompasses several meanings.

In one sense, it can refer to devices that serve as an entry point into different networks, acting as gateways from one network to another. Routers are an important example of edge devices, as are routing switches and devices that provide access to SD-WANs (software-defined wide area networks). In some instances, a firewall can be used for the same purpose of bridging networks. Likewise, edge servers are another form of edge device, and they also provide a means for entering another network.

But that’s just one of its interpretations. The term also covers edge computing devices typically classified under the Internet of Things (IoT) designation, which are engineered to collect and wirelessly transmit data. IoT devices include various types of actuators, appliances, and sensors and are found in wide use by consumers and industries alike.

It’s been projected that by 2030, there will be nearly 30 billion IoT devices in use around the world. Considering that projection represents a gain of nearly 13 billion devices over 2024 levels, it’s obvious the number of IoT devices in use will climb substantially and dependably as the technology continues to be integrated into more and more households and factories globally.

For both markets, IoT devices take many forms. The consumer marketplace includes IoT devices as varied as smart home devices (e.g., refrigerators, lighting appliances, thermostat and home-security controls), enhanced payment terminals and even wearable technology.

On the industrial front, IoT devices bolster supply chain processes by constant monitoring of variables like assigned routes (and any traffic complications), the weights of loads being shipped, and required container temperatures. Industrial IoT devices also aide in other key business processes, like asset tracking, predictive maintenance and quality control safeguards. Further, industrial IoT apps and devices empower cutting-edge pursuits, such as the drone-based delivery of goods.

For organizations wrestling with overloaded data center problems, edge networks offer plenty of useful benefits.

The top benefit offered by edge networks is increased data transmission rates with better throughput, as enabled by decreased latency and as compared to regular networks. These download speeds can hit 384 Kbps (or between two and three times faster than regular networks).

Edge networks also help organizations do a better job of policing their own networking services from a network security perspective, bolstering those efforts with added access control, packet inspection and data decryption. Edge networks also add a complete layer of cybersecurity to network cores.

In order to achieve its steady throughput, edge networks can be identified by the high bandwidth typically associated with edge computing. In edge networks, this pronounced bandwidth is combined with greatly reduced latency that improves the real-time access of network information.

One key feature of edge networks is their dependability. Credit the near-omnipresence of edge devices. These both store and process data and work in conjunction with edge data centers to counter and overcome any occasional network connectivity issues they may experience.

Edge networks were created in response to a problem. To track their origin accurately, it’s necessary to discuss the evolution of hyperscale data centers—which were also created in response to a problem. While it’s certainly true that many smaller organizations and mid-size companies can derive definite benefits from edge networks (such as enhanced scalability), it’s also true that edge networks were originally developed as a counter-measure to remedy the situation of overcrowded hyperscale data centers, which by their nature tend to be massive and of most use to larger companies that can afford their exorbitant price tag, which can run into USD millions or even billions.

This all began in the 1990s when content delivery networks (CDNs) first started being used. A CDN is a group of servers that are geographically distributed and enable the caching of content closer to users. CDNs enabled the provisioning of web/video content and its storage in data centers.

Data centers were an outgrowth of defined concepts such as cloud computing and virtualization. However, by the early 2000s, many businesses started outgrowing their on-premises data centers, which spurred the creation of hyperscale data centers built or rented through colocated facilities. Further, for many organizations, more scalability was needed in addition to more storage space to handle their massive workloads.

Hyperscale data centers offered that desired scalability, plus the ability, space and bandwidth to spin up various apps within hyperscale facilities as needed. Soon these hyperscale data centers began popping up around the globe, offering network computing on an aggressively macro scale. The industry definition of hyperscale data center, as created by International Data Corporation (IDC), holds that to qualify as a true hyperscale data center, such a facility has to use at least 5,000 servers and occupy at least 10,000 square feet of floor space.

And that leads us to the current problem of hyperscale data centers, which, ironically, are now experiencing data storage issues. When many companies adopted hyperscale data centers, they assumed they now had enough room and bandwidth to store all possible forms of data. And indeed they did, but at a cost: increased latency and decreased data transmission rates. The result? Some of these hyperscale data centers have become so crammed to capacity that they can barely run with any success.

This problem created the need for edge networks to be developed. Since their introduction, edge networks have rapidly become a valued go-to solution for the modern company that deals with data. Industry analyst Gartner studied the edge network situation in 2023 and reported that 69% of the CIO respondents sampled indicated that their organizations either had already begun using edge computing solutions or planned to do so by mid-2025.

In terms of the US market alone, you can see the near-explosive growth and acceptance of edge network technology. A Global Edge Computing Market Report held that the US market had an edge-network market size of USD 7.44 billion in 2021. The same set of market-analysis value projections forecasted a staggering 2030 value projection of USD 157.9 billion. This equates to a steady and substantial 37.9% growth rate from year to year.

While hyperscale data centers did and do allow companies superior scalability, they are still subject to the same capacity problems associated with regular data centers, meaning that the more data “freight” they’re carrying, the more susceptible they are to slower data transmission rates.

Edge networks act to decongest network infrastructure so latency rates can be reduced and transmission speeds can be increased. Edge networks accomplish this by embracing the design of a distributed network model, in which various computing tasks are distributed to a variety of assets for general load balancing and boosting data speeds.

The center of the edge network houses its processing core (almost like the nucleus of an atom). The endpoints that radiate outward from that central location are like stationary atoms at the far reaches of the molecule. In the edge network model, these endpoints (or nodes) are where edge devices are located—whether their function is to link networks or to perform a wide variety of processing chores.

Distributed networks take on extra power when they join forces with edge computing hardware, producing a synergistic situation in which the heightened performance of distributed networks is combined with the lower latency amounts associated with edge networks and edge devices.

The following industries and use cases can all find great usefulness in implementing an edge network.