Network Edge 5G Computing Technologies Predicted to Make Dramatic Changes to Business Operations

Recently, we saw the strange news that Verizon is installing chest freezer-sized power transformers in people’s front yards. The reason? The transmitters that are fundamental to the roll out of 5G networks across the country have terrible range, and need to be installed on many utility poles in a particular area to give good coverage. This in turn means many new electricity transformers, despite local residents’ concerns about this new equipment.

Though arguments like this continue to characterize the roll-out of the 5G network across the country, businesses have quietly accepted the inevitable, and have begun to prepare for a future where 5G is the standard wireless networking protocol. These preparations have allowed many such businesses to recognize that much of the computing currently done in huge data centers can now be moved to the network edge, and shared between many 5G-enabled devices.

Implementing network edge 5G technologies can offer many advantages in terms of faster, more efficient business operations. Using this approach, however, also presents challenges for business ops teams, from deploying edge cloud solutions without sacrificing security, to simply dealing with vast quantities of extra data. In this article, we’ll take a look at both aspects of network edge 5G models – the promise, and the risk.

Network business operations

Before we get into the technical side of 5G edge networks, it’s worth taking a moment to consider why this type of network is going to be useful for business operations, and why this model has been so widely adopted in many industries.

The answer is actually quite straightforward. Network edge 5G networks provide a roadmap to a truly programmable IoT, and this will make business operations much more agile, adaptable, and responsive. This is why we’ve seen such explosive growth in first-generation  IoT across a whole range of sectors – from industrial and hospitality robotics to industrial drones and autonomous vehicles.

Though these developments are exciting, embracing them also presents challenges for the average firm. IoT networks typically require huge amounts of data processing “behind the scenes”, and this needs to be done in real-time in order to make these networks as responsive as they can be. 

Given this, it’s quickly becoming apparent that the “traditional” model through which embedded devices have been managed – centralized data centers – is no longer fit for this purpose. Instead, processing duties are now increasingly being offloaded to consumers' smartphones or to nearby cloud servers. In other words, processing is moving closer to devices, and closer to the network edge.

This shift has, in turn, catalyzed the development of a number of parallel technologies and approaches. One has been to break monolithic cloud processing and storage repositories into a number of smaller cloudlets. 

Another, fueled by the need of small businesses to prevent cyberattacks through their IoT networks, has been to deploy interstitial data processing hardware between IoT devices and public clouds, in order to ensure that the minimum possible amount of sensitive data is shared over public networks. 

5G at the edge

More and more processing is being done on devices themselves, or at least on interstitial devices that sit between IoT nodes and centralized data centers in the network hierarchy. All of these devices need to share data, and they need to do so quickly and reliably. The only real option for doing so is the 5G network.

This is because the speed of a 5G network is at least ten times faster versus what 4G can offer. This increased speed will free up both operations staff and developers, because they will no longer have to work around hardware limitations when it comes to putting in place truly adaptive IoT systems. These systems can, for instance, greatly improve the efficiency of warehousing and shipping processes, but also revolutionize the way that the end consumer interacts with your products.

This shift is not a niche concern, either. In fact, it’s big business. A recent report from Allied Market Research found the edge computing market registering an annual growth rate of nearly 33% worldwide until 2025. The report also made the case that edge computing is only going to gain in popularity as 5G capabilities are rolled out across the country.

The business impacts of 5G edge

Though it’s clear that 5G network edge computing is going to have major impacts on a wide variety of sectors, for those working in business operations it can be difficult to envisage how, exactly, these networks will make a difference to day-to-day decision making and resource deployment. 

Let’s take a look at a few specific examples of this.

Device-centric design

Perhaps the biggest impact of the 5G network edge model, albeit the one that will also take the longest to be seen in the “real world”, is that this fundamentally changes the way in which consumer-facing devices are designed. 

Instead of devices being a manifestation of processes and data held in a centralized cloud, they will regain some of the independence they lost in the era of networking. Cloud computing expert Barbara Ericson of Cloud Defense explains what this independence looks like: “You can use the same software or program from your mobile device, like a smartphone or tablet, your desktop, and your laptop without individually downloading and installing that program each time. This is invaluable for companies in particular that need all of their workplace computing devices to utilize the same programs consistently.”

For many business operations teams, this shift will look like a return to a model believed to be obsolete. Instead of designing devices that merely send data to the cloud, teams should begin to think about how the devices they have already deployed – from the apps on consumer phones to IoT sensors in manufacturing machinery – can use the data they are already collecting, and use it to generate useful business intelligence. 

Adaptive IoT provisioning

Another revolutionary aspect of the development of 5G edge networks is that, since devices will be more autonomous than they are today, business operations teams will be able to control their computing resources with a finer degree of granularity than ever before.

This will make it possible, for instance, for IoT devices to operate largely independently for a larger proportion of the time. It will also allow the deployment of continuous delivery and continuous integration models on IoT devices, so that the firmware they run on is always up-to-date and can be quickly adapted to changing business needs.

In the broadest sense, this ability may make it possible for IoT networks to be designed by business intelligence specialists, rather than developers and technical staff. This is because, with adaptive provisioning over 5G networks, IoT networks can be designed around generic devices that provide a range of sensing and effective capabilities, rather than the extremely specialized devices that such networks rely on today.

Specialized and generic networks

Another impact of the growing popularity of network edge networks is having the opposite effect to the one I’ve just mentioned: in recent years we’ve seen a number of highly specialized networking solutions emerge. While IoT devices are becoming more generic, in other words, the networks they run on are becoming more specialized.

This can be seen in a number of ways. One, for instance, is the fact that the 5G network is already being broken into a number of private spectrums for enterprises, in order to keep IoT networks from interfering with each other. Another is the simultaneous rise of Infrastructure as Code (IaC) solutions, which seek to abstract the complexities of edge computing into reliable, repeatable frameworks that can be manipulated and worked with by operational teams.

In terms of business operations as a whole, it’s possible that these solutions have a strange effect – removing the perception that edge networks are being used at all. In fact, the whole paradigm that underpins the network edge methodology – in which the complexity of networks largely depends on device functionality – has the effect of erasing the distinction between client and server, and as such between device and network.

In practice, this means that many of the IoT networks that have already been purchased by business operations teams are already running on an edge model, and may well be already be making use of 5G where this is available. 

Improving device connectivity

Finally, it’s important to recognize that the advent and widespread adoption of edge networks is going to have an impact on the popularity and development of 5G networks themselves. In fact, the relationship between 5G and the IoT is so close that it is often difficult to isolate which technology is driving the other.

For instance, during the last year we’ve seen much research into the way in which the latency inherent to 5G networks may be reduced, largely in order to improve the speed at which IoT networks can operate. Once research like this starts to bear fruit, it will then have a knock-on effect on almost every aspect of business operations, simply because sending data from one system to another will be increased.

In other words, we are now witnessing a positive feedback loop, in which every advance in IoT technology spurs development of the 5G network, and vice versa.

The challenges of 5G network edge

It’s not all good news when it comes to 5G network edge solutions, though. It’s also important to recognize that these systems are still in their infancy, and many challenges remain to be overcome before business operations teams can use them with complete confidence.

These challenges can be broken down into two key factors. 

The first is that business teams are frequently called upon to work with a huge variety of different devices, and without a corresponding increase in the level of resources devoted to protecting them. This challenge is compounded by another: that IoT networks inherently make use of multiple channels and devices, making security scanning increasingly complex. 

The second is simply the long-term concern that the security industry may not be able to keep up with the speed of 5G networks when it comes to protecting connected communication devices and stopping the flow of malware across those devices. With AI-enhanced cyberattacks able to develop at lightning speed and a new mobile device attack occurring every 39 seconds on average, it may be that a completely new type of network perimeter protection is needed to protect 5G network edge systems and the devices connected to the network.

The bottom line

Business operations has always been a highly dynamic and fast-moving industry, and one that requires professionals to be continually on the lookout for the next big shift. Given how many edge 5G networks are already in use, it seems all but certain that this technology is poised to provide the next revolutionary shift in the way we develop and deploy industrial and consumer devices. 

For this reason, it’s crucial that operations teams take the opportunity to embed IT operations within wider teams, in order to ensure that the everyday management of these networks and devices is not forgotten in the rush to deploy them. If that can be done, however, a bright future awaits. 

About the Author

Sam Bocetta is a former security analyst, having spent the bulk of his as a network engineer for the Navy. He is now semi-retired, and educates the public about security and privacy technology. Much of Sam’s work involved penetration testing ballistic systems. He analyzed our networks looking for entry points, then created security-vulnerability assessments based on my findings. Further, he helped plan, manage, and execute sophisticated "ethical" hacking exercises to identify vulnerabilities and reduce the risk posture of enterprise systems used by the Navy (both on land and at sea). The bulk of his work focused on identifying and preventing application and network threats, lowering attack vector areas, removing vulnerabilities and general reporting. He was able to identify weak points and create new strategies which bolstered our networks against a range of cyber threats. Sam worked in close partnership with architects and developers to identify mitigating controls for vulnerabilities identified across applications and performed security assessments to emulate the tactics, techniques, and procedures of a variety of threats.