The Benefits, Potential, and Future of Edge Computing
By: Kaylie Gyarmathy on April 29, 2021
For organizations looking to break beyond the limitations that traditional cloud-based networks impose, edge computing can make all the difference.
Although cloud computing continues to play an important role in modern network architecture, the exciting possibilities offered by Internet of Things (IoT) devices, which are capable of processing the data they gather closer to the source, are forcing companies to rethink their approach to IT infrastructure.
Often touted as the “next big thing,” many companies are wondering how edge computing differs from more traditional data processing solutions and how it could benefit their business. While the basic principles behind edge computing are relatively straightforward, the substantial benefits of this new approach to network architecture are a little more complex. Edge computing not only has the ability to deliver a direct on-ramp to a company’s preferred cloud platform, but it also can help achieve flexibility and nimbleness when it comes to ensuring a streamlined, efficient IT infrastructure.
Whether they’re trying to break into the IoT market or find better ways to deliver content services, companies need to be aware of the advantages and the future of edge computing.
Traditional cloud computing networks are highly centralized, with data being gathered on the outermost edges and transmitted back to the main servers for processing. This architecture grew out of the fact that most of the devices located near the edge lacked the computational power and storage capacity to analyze or process the data they collected. Even as more devices became capable of connecting to networks over cellular and WiFi, their functionality was relatively limited by their hardware capabilities.
As a result of the miniaturization of processing and storage technology, the network architecture landscape has been significantly altered.
Today’s IoT devices are capable of gathering, storing, and processing more data than ever before. This opens up opportunities for companies to optimize their networks and relocate more processing functions closer to where data is gathered at the network edge. There, it can be analyzed and applied in real-time much closer to intended users.
Since the data doesn’t have to travel all the way back to the central server for the device to know that a function needs to be executed, edge computing networks can greatly reduce latency and enhance performance. The speed and flexibility afforded by this approach to handling data create an exciting range of possibilities for organizations.
Let’s take a look at five benefits of edge computing when it comes to improving the overall performance of your network.
Five Benefits of Edge Computing
Speed is absolutely vital to any company’s core business. Take the financial sector’s reliance upon high-frequency trading algorithms, for example. A slowdown of mere milliseconds in their trading algorithms can result in expensive consequences. In the healthcare industry, where the stakes are much higher, losing a fraction of a second can be a matter of life or death.
For businesses that provide data-driven services to customers, lagging speeds can frustrate customers and cause long-term damage to a brand. This may not sound as serious as life and death, but poor network performance and slow speeds can spell the end of your company altogether. Speed is no longer just a competitive advantage—it’s a best practice.
Edge computing’s most significant benefit is its ability to increase network performance by reducing latency. Since IoT edge computing devices process data locally or in nearby edge data centers, the information they collect doesn’t have to travel nearly as far as it would under a traditional cloud architecture.
In today’s world, it’s easy to forget that data doesn’t travel instantaneously; it’s bound by the same laws of physics as everything else in the known universe. Current commercial fiber-optic technology allows data to travel as fast as 2/3 the speed of light, moving from New York to San Francisco in about 21 milliseconds.
However, as more and more data continues to be transmitted, digital traffic jams in the future are almost a sure thing. In 2020, the world generated roughly 44 zettabytes (one zettabyte equals a trillion gigabytes) of data. By 2025, 463 exabytes (one exabyte equals a billion gigabytes) of data will be generated every day.
By processing data closer to the source and reducing the physical distance it must travel, edge computing can greatly reduce latency. This means higher speeds for end-users, with latency measured in microseconds rather than milliseconds. Considering that even a single moment of latency or downtime can cost companies thousands of dollars, the speed advantages of edge computing are paramount to your network.
While the proliferation of IoT edge computing devices does increase the overall attack surface for networks, it also provides some important security advantages. Traditional cloud computing architecture is inherently centralized, which makes it especially vulnerable to distributed denial of service (DDoS) attacks and power outages. Edge computing distributes processing, storage, and applications across a wide range of devices and data centers, which makes it difficult for any single disruption to take down the entire network.
One major concern about IoT edge computing devices is that they could be used as a point of entry for cyberattacks, allowing malware or other intrusions to infect a network from a single weak point. While this is a genuine risk, the distributed nature of edge computing architecture makes it easier to implement security protocols that can seal off compromised portions without shutting down the entire network.
Since more data is being processed on local devices rather than transmitting it back to a central data center, edge computing also reduces the amount of data actually at risk in a single moment. There’s less data to be intercepted during transit, and even if a device is compromised, it will only contain the data it has collected locally rather than the trove of data that could be exposed by a compromised central server.
Even if an edge computing architecture incorporates specialized edge data centers, these often provide additional security measures to guard against crippling DDoS attacks and other cyber threats.
As companies grow, they cannot always anticipate their IT infrastructure needs. Building a dedicated data center is an expensive proposition, which makes it even more difficult to plan for the future.
In addition to the substantial up-front construction costs and ongoing maintenance, there’s also the question of tomorrow’s needs. Traditional private facilities place an artificial constraint on growth, locking companies into forecasts of their future computing needs. If business growth exceeds expectations, they may not be able to capitalize on opportunities due to insufficient computing resources.
Fortunately, the development of cloud-based technology and edge computing has made it easier than ever for businesses to scale their operations. Computing, storage, and analytics capabilities are increasingly being bundled into devices with smaller footprints that can be situated nearer to end-users.
Expanding data collection and analysis no longer requires companies to establish centralized, private data centers, which can be expensive to build, maintain, and replace when it’s time to grow again. By combining colocation services with regional edge computing data centers, organizations can expand their edge network reach quickly and cost-effectively. As they grow, the flexibility of leveraging edge computing's capabilities allows them to adapt quickly to evolving markets and scale their data and computing needs more efficiently.
In short, edge computing offers a far less expensive route to scalability, allowing companies to expand their computing capacity through a combination of IoT devices and edge data centers. The use of processing-capable edge computing devices also eases growth costs because each new device added doesn’t impose substantial bandwidth demands on the core of a network.
The scalability of edge computing also plays into its versatility. By partnering with local edge data centers, companies can easily target desirable markets without having to invest in expensive infrastructure expansion.
Edge data centers allow them to service end-users efficiently with minimal physical distance or latency. This is especially valuable for content providers looking to deliver uninterrupted streaming services. They also do not constrain companies with a heavy footprint, allowing them to nimbly shift to other markets if economic conditions change.
Edge computing empowers IoT devices to gather unprecedented amounts of actionable data. Rather than waiting for people to log in with devices and interact with centralized cloud servers, edge computing devices are always on, always connected, and always generating data for future analysis.
The unstructured information gathered by edge networks can either be processed locally to deliver quick services or delivered back to the core of the network, where powerful analytics and machine learning programs will dissect it to identify trends and notable data points. Armed with this information, companies can make better decisions and meet the true needs of the market more efficiently.
By incorporating new IoT devices into their edge network architecture, companies can offer new and better services to their customers without completely overhauling their IT infrastructure. Purpose-designed devices provide an exciting range of possibilities to organizations that value innovation as a means of driving growth. It’s a huge benefit for industries looking to expand network reach into regions with limited connectivity (such as the healthcare, agricultural, and manufacturing sectors).
Given the security advantages provided by edge computing, it shouldn't come as a surprise that it offers better reliability as well. With IoT edge computing devices and edge data centers positioned closer to end-users, there is less chance of a network problem in a distant location affecting local customers. Even in the event of a nearby data center outage, IoT edge computing devices will continue to operate effectively on their own since they handle vital processing functions natively.
By processing data closer to the source and prioritizing traffic, edge computing reduces the amount of data flowing to and from the primary network, leading to lower latency and faster overall speed. Physical distance is critical to performance as well.
By locating edge systems in data centers geographically closer to end-users and distributing processing accordingly, companies can greatly reduce the distance data must travel before services can be delivered. These edge networks ensure a faster, seamless experience for their customers, who expect to have access to their content and applications in an instant anywhere, anytime.
With so many edge computing devices and edge data centers connected to the network, it becomes much more difficult for any singular failure to shut down service entirely. Data can be rerouted through multiple pathways to ensure users retain access to the products and information they need. Effectively incorporating IoT edge computing devices and edge data centers into a comprehensive edge architecture can therefore provide unparalleled reliability.
Edge Computing and IoT
The number of IoT devices in circulation today is already staggering, and there’s plenty of data to suggest that this figure will increase significantly in the coming years. With so many IoT devices connected to networks around the world, edge computing is already having a major impact on how companies design their systems.
The ongoing demand for faster, more efficient services and content delivery will push organizations to improve their existing edge networks. Companies that fail to invest in edge computing today could find themselves in the unenviable position of scrambling to catch up to their competitors in the years to come.
The data generated from devices connected to the internet provides an enormous opportunity for businesses. But with that opportunity comes accompanying challenges in regards to managing, analyzing, and storing that data. Traditionally, these processes were handled in a company’s private cloud or data center, but the sheer volume of data has pushed these networks to their absolute limits.
Edge systems alleviate this pressure by pushing data processing away from a centralized core and distributing it among local edge data centers and other devices closer to the source. Analyzing data closer to where it’s collected provides huge benefits in terms of cost and efficiency. By utilizing edge systems, companies can also address problems associated with low connectivity and the cost of transferring data to a centralized server.
The Future of Edge Computing
Shifting data processing to the edge of the network can help companies take advantage of the growing number of IoT edge devices, improve network speeds, and enhance customer experiences. The scalable nature of edge computing also makes it an ideal solution for fast-growing, agile companies, especially if they’re already making use of colocation data centers and cloud infrastructure.
By harnessing the power of edge computing, companies can optimize their networks to provide flexible and reliable service that bolsters their brand and keeps customers happy.
Edge computing offers several advantages over traditional forms of network architecture and will surely continue to play an important role for companies going forward. With more and more internet-connected devices hitting the market, innovative organizations have likely only scratched the surface of what’s possible with edge computing.
As the Marketing Manager for vXchnge, Kaylie handles the coordination and logistics of tradeshows and events. She is responsible for social media marketing and brand promotion through various outlets. She enjoys developing new ways and events to capture the attention of the vXchnge audience.