Whether you run a chain of retail stores, a plant manufacturing toys or mobile phones, or an autonomous drone fleet, you'll have heard about what edge computing can do for you.
Edge computing has been with us in rudimentary form since the nineties, but it's in the multiconnected world of cloud, Internet of Things and digital supply chain logistics that it's really taking off.
Modern data collection and processing technologies have meant edge computing systems have the storage and analytical power to act on the data they gather at the location of the machine, device or node that produces it. It does what cloud computing does on a smaller scale, right on the device.
And it's growing. According to one report, over 50% of information created by devices like IoT devices will be processed at the edge next year, a total of just over 73 zettabytes globally.
It's taken hold because of the need for faster data transport, higher definition content and lower latency. More bandwidth-intensive data needs and more devices connected to the internet than ever has given edge computing the edge (so to speak). Below, we list the benefits that this technological boom will bring.
1. Customer experience
The most widely experienced benefit of edge computing is its ability to increase network performance by reducing latency. Since IoT edge devices process data locally or in micro data centres, the information they collect and distribute doesn't have to travel anywhere near the same distances as it would with cloud architecture.
The 'edge' refers to the location where users and their devices meet. It's a distributed platform that extends as far as possible towards the customer, cutting distances and, subsequently, the time it takes for them to be served, achieving higher bandwidth. All this goes some way to making data travel faster, meaning higher speeds for end-users.
2. Security
Edge computing is finding a natural home in cyber security. The practice of decentralizing data processing helps reduce the risks associated with storage in a central silo or repository.
Cloud computing needs information to be collected, packaged and sent to centralized servers, potentially exposing it to hijacking during transit, not to mention the security vulnerabilities of many storage systems.
By contrast, processing data locally on your device reduces or removes those risks entirely because sensitive information doesn't need to travel across networks where cyber criminals lie in wait.
In fact, edge computing is also set to benefit cyber security itself through improved threat detection and response. Devices at the edge can collect and process data to produce real-time analytics that might identify anomalous activity faster than a human operator can spot it.
And the numbers don't lie. According to a 2023 report, organisations using edge computing in their cyber security efforts saw threat incident response times go down by 25%.
Edge computing also supports expanded security frameworks like device-level encryption and authentication, maintaining data integrity from the source, and the reduced need to transmit data lowers the risk of it being intercepted.
3. Real-time analytics
Edge computing enhances real-time analytics processing because bringing data closer to the source reduces the latency and use of bandwidth. When information is collected and sent from Internet of Things (IoT) devices to a server or cloud service, delays can creep in – especially as data volume goes up.
Because edge computing performs the processing at the source of the collection, analytic results are processed and delivered almost immediately, and in some applications like steering or braking an autonomous vehicle, delays can mean life or death.
Analytics also benefits by providing constant or rolling results as data flows from the process, not just immediately but updating on the fly. When applied to fields like predictive maintenance, or machinery performance to forecast failures or choke points, it can mean the difference between swapping out a part during scheduled maintenance downtime or your whole operation grinding to a halt.
4. Scalability
Scalability might be one of the least discussed (but no less important) business practices edge computing enables.
Enterprises have traditionally relied upon dedicated, purpose-built data centres, but they don't always represent the best value when you take the set-up and maintenance costs into consideration. It might also constrain growth to some extent because you'll find yourself locked into systems or contracts with specific providers or environments and miss out on technological improvements happening elsewhere.
Edge computing also connects IoT devices to micro data centres, which further reduces costs by removing the need to subscribe to a dedicated data centre. Like cloud computing builds, micro data centres can scale up quickly and easily to handle spikes in sales or workload, or give you environments in which to test and develop new applications or features.
What's more, their standardized, prefabricated nature ensures they can be integrated seamlessly – establish a new one and when it's full, simply spin up another one.
5. AI models
Edge computing stands to revolutionise the development and deployment of machine learning products like complex multimodal computer vision models, with on-board data collection and processing much more efficient than sending data to offsite cloud computing environments.
Multimodal AI models use training data from multiple sources and file types – everything from images and video to sensor inputs – to make predictions. As edge computing removes or reduces data latency, the results are much faster. In just one example, smart surveillance systems with multimodal computer vision can analyse multiple inputs like video feeds and environmental sensor data, spotting unusual behaviour or patterns and alerting householders or security staff to anything that looks awry.
What's more, when it comes to AI systems that provide security or safety, edge computing provides an always-on architecture. If power or network connectivity is intermittent or goes off unexpectedly, the system can still function.
6. Interoperability
Edge computing can also protect you against obsolete networks and architectures. Devices are capable of acting as a bridge between legacy and current hardware or software environments, integrating every system you use so you can extract the highest possible ROI from IT investments.
It's no accident edge computing made its name in industrial settings – manufacturers and heavy machinery operators can't afford to abandon a whole workflow, control system software, or machinery fleet just because something newer or cooler comes along, and edge computing frameworks provided the landscape to connect the old with the new seamlessly.
As always, integration isn't easy – or cheap. But it's long been considered a critical issue in the field, so a lot of research and programming is going on right now to help older and newer devices interact and communicate. One direction that's being widely pursued is open source interfaces, but even with the cost and training burden, it can be a more effective way forward.
