With the emergence of the Internet of Things (IoT) and 5G, it seems that everything around us is connected. On the one hand, it opens up a world of new possibilities, like self-driving cars and smart cities. But, on the other hand, the sheer number of devices and data can burden networks and threaten to shut them down.
This dilemma is the driving force for edge computing – a new way to store, analyze, and process data nearer the source. This decentralization promises to unclog network congestion and improve overall network performance.
Edge computing is a decentralized IoT methodology where data processing and storage are performed on or closer to the network’s edge, where individual IoT devices are located. To understand the edge computing definition, it’s essential first to examine what a traditional IoT network looks like.
Most IoT networks adopt a centralized client-server architecture. Take the website you’re viewing this article on, for example. All the text and photos of the webpage are housed on a web server. The browser on your mobile phone or computer (the “client”) needs to connect to this server to get the webpage data and display it on your screen.
The problem with the client/server approach is that it’s a centralized system. If there’s a huge number of concurrent users and data traffic, it can clog the server and its network. This can lead to a slowdown in performance. What’s more, in this model, the server is a weak link. If it goes down, the entire system goes down with it.
Devices that are located further away from the server will also introduce some delay, called latency. Since it’s physically impossible to go faster than the speed of light, such delays are unavoidable with substantial geographical distances. The result is that web pages and applications run slower.
This lag problem is unacceptable with IoT devices that need to work in real-time. For example, can you imagine if the IoT sensor of a smart car experiences a delay? It could result in a catastrophic accident.
Edge computing solves the dilemma by delegating processing and storage load throughout the network. Instead of dumping all tasks on a central server, some of it is passed on to IoT devices on the network’s edge. Once processing is done, only relevant data is sent back to the central server for monitoring and storage.
For instance, take an IoT sensor that monitors the condition of a factory’s equipment. Rather than transmit vast volumes of raw measurement data to a server, some can be processed on-site. Only select data, such as which machines need maintenance work, are sent back to the server.
An edge device is a machine on the edge network that handles storage, data processing, and input/output operations. In most cases, this will be your IoT or consumer device, such as a computer or mobile phone.
The function and limits of an edge device differ significantly, depending on the industry. For instance, edge devices in healthcare are often in the form of wearable devices and implants. These are responsible for measuring patients’ vitals and, in some cases, even responding based on these measurements. They’re also often used to personalize a person’s treatment plan.
In some cases, there can be several devices that act like a collective edge device, forming a “mini client-server network.” Manufacturers, for example, employ edge IoT devices like sensors to measure equipment performance and track inventory. These devices transmit data to an on-site computer (an edge device called an edge gateway) that processes the data and forwards them to the central server.
Edge devices help alleviate the processing load from the central server and enhance overall security. They can act as gateways that can block malicious attacks from reaching the central server; if a hack occurs, only that part of the edge network is affected, leaving the rest unscathed.
The decentralization that edge processing opens up the possibility of critical real-time applications with IoT technology, such as self-driving cars and smart city traffic systems. This is because such an approach helps overcome several physical network limitations – notably bandwidth, congestion, and latency.
Bandwidth is the amount of data that can flow through a network. Because of underlying network hardware and physical distances, there’s a limit to this capacity. And even if a faster technology like 5G is coming, there will still be an upper limit to bandwidth.
The bandwidth limitations also create congestion, simply because the volume of data coursing through the Internet today is staggering.
Data capacity isn’t the only problem; there’s also the issue of latency. The reality is that a signal moves only at a finite speed from point A to point B, no matter how light the network bandwidth is. As a result, there will always be a delay when the data is sent to the time it’s received. The greater the distance, the bigger the delay.
Instead of overcoming these limitations, edge computing adopts a smarter way by simply decentralizing the network. This effectively reduces the distance data needs to travel for processing (eliminating latency) and lessens the load on the network’s bandwidth (solving congestion).
And, as we’ve mentioned, security and privacy are also among the best benefits of edge computing. This becomes increasingly important with IoT devices that might not have the robust security features as your smartphone or laptop.
For instance, your smart fridge might be a more juicy target than your iPhone with Face ID and password protection. But with edge computing, an edge gateway can have protections of its own to prevent hackers from getting further into the network.
Finally, there are two more benefits of edge computing that bear mentioning: compliance and autonomy.
Data can’t always be moved from one location to another due to conflicting privacy laws. For instance, transferring data to and from the European Union must comply with GDPR guidelines. However, edge computing can ensure compliance by storing and processing sensitive data within the regulation’s jurisdiction. This makes it the preferred approach of industries that handle sensitive personal data, like finance and healthcare.
Autonomy also allows the edge layers to function independently, regardless if it’s connected to the primary network or not. This is a boon for operations on remote locations with unreliable or zero Internet connectivity, such as mines or oil rigs.
Many exciting use cases and possibilities exist with IoT, which can be improved further with edge computing. Let’s cover some of them.
Take a company’s network of security cameras, for instance. By default, it will record and send footage back to HQ for monitoring and archiving. Now imagine the congestion that will happen to your network if you have hundreds of them.
The solution is AI. Because most camera footage is useless, an AI system at the edge can pick only the crucial footage to send to HQ while storing the rest locally.
The practical approach here is edge computing. Metrics like speed, location, traffic conditions, and other variables can be processed in the car’s onboard computer. That way, only relevant data needs to be sent to a hub for monitoring.
However, the issue is that retail stores in various locations will have different environments and factors that need to be considered. Thus, it’s more beneficial to use edge computing to process these data locally.
Almost every industry on Earth can benefit from IoT and edge computing technology. We’ve already mentioned some of them, including security and retail. But generally, the sectors that benefit most from edge computing are those where real-time performance is critical. These include manufacturing and automotive. Any downtime in these industries will have catastrophic consequences, both in lives and money. Industries that deal with sensitive data are also a prime candidate for edge computing, like banking and healthcare.
Edge computing is undoubtedly a powerful approach that can increase your network’s performance, security, and privacy.
Choose a provider like Fusion Connect – with a suite of networking and security solutions and extensive industry experience - to make it work for your business.
Contact us today, and let’s explore how you can implement edge computing into your network.