Living on the Edge
Somewhere between cloud computing and local networks, edge computing is stepping into the field as a highly capable candidate for the title of next computing standard. Will it become the new paradigm for the next decade? Time to talk about why edge computing is something you’ll want to keep a close eye on.
If you look at the history of computing from a broad perspective, there seems to be a pendulum movement switching back and forth between centralised and decentralised control. In the early days of computing, centralised mainframes controlled ‘dumb’ terminals. With the advent of the personal computer and local networks in the ’80s, a new era of decentralised computing unfolded. Much more recently, client-server architecture made the pendulum switch back to the centralised trend with cloud computing pioneers like Amazon (AWS), Google (GCP) and Microsoft (Azure).
Today, the pendulum is swinging back again as we continue to evolve towards an increasingly connected world. The rapidly growing IoT industry, the deployment of fast 5G networks, ever more potent end-user devices and new types of applications are pushing for new kinds of computing models. Will the pendulum come to a halt in the middle with the rise of edge computing?
Opportunities beyond the edge
In case the term ‘edge computing’ sounds a bit blurry to you, let’s try to define it. Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth.
New applications, limited by the restrictions of existing centralised cloud solutions, are forcing us towards this new approach of edge computing. According to Gartner, more than 15 billion IoT devices will connect to the enterprise infrastructure by 2029. Combining edge computing techniques with new and existing technologies like IoT, cloud computing, big data and AI/ML will enable a range of new applications for smart homes, smart factories (Industry 4.0), connected vehicles, energy supply and health monitoring, to name just a few. But what exactly does edge computing have to offer?
Around 10% of enterprise-generated data is created and processed outside a traditional centralised data centre or cloud. By 2025, Gartner predicts this figure will reach 75%.
The advantages of edge computing
Under the bonnet of every shift in the digital landscape, there’s always a powerful engine. Apart from sounding fancy, we need to look at what is pushing the pendulum back towards more decentralised structures. What does edge computing have to offer that’s attractive for both industries as users?
- Less latency
Edge computing finds its origin in the early CDNs (Content Distribution Networks) where caching servers would be placed in places geographically closer to the end-user to reduce latency. The physical limitation of signal latency is not acceptable in mission-critical applications expected to give near real-time performance.
- More autonomy
Bringing computing closer to end-users reduces the chance of network problems in a distant location affecting local customers. And it can bring connectivity to places where there’s no connection at all. Even in the event of a nearby outage, the edge devices will continue to operate effectively on their own.
By filtering out irrelevant data on the edge, one can reduce network bandwidth, data storage and processing in the centralised cloud. Spreading this ‘pressure’ could significantly affect the running cost of a cloud platform.
- A win for privacy
Applications that require private data can benefit from edge computing as well. Instead of analysing all private data in one centralised cloud, advanced machine learning models could be deployed on the edge. The private data of end-users can be processed much closer and quicker, limiting the risk of a breach in the cloud exposing data.
The edge in practice
Leaving theory to one side, let’s look at some interesting case uses for edge computing. Take autonomous vehicles, for instance. When we’re thinking about autonomous vehicles, Tesla and their self-driving cars will almost certainly pop into our heads first. But most likely the first use cases of real autonomous driving will be truck platooning.
Truck platooning is the linking of two or more trucks in a convoy, using connectivity technology and automated driving support systems. These vehicles automatically synchronise their speeds and routes and maintain a close distance between each other. The truck at the head of the platoon acts as the leader while the trucks behind it will react and adapt to changes in the leader’s movement. This new way of transportation, working on the principles of edge computing, offers quite a few benefits:
- Ecological: Given that trucks can drive closer together, the air resistance force is reduced significantly and will result in lower fuel consumption and CO2 emissions.
- Safety: IoT sensor data is analysed on the vehicle edge to provide automated and immediate responses, like breaking. Vehicles following the leading truck only need a fifth of the time a human would need to react, thus improving safety.
- Efficiency: Platooning optimises transport by using roads more effectively, delivering goods faster and reducing traffic congestion
Changing entire industries
Edge computing isn’t limited to very specific use cases; it’s likely to affect entire industries, such as the life sciences sector. Before 2020, digital transformation in healthcare was pretty slow, but over the past year, the industry has speeded up efforts to embrace digital transformation. The sky’s the limit when it comes to the opportunities for using edge computing in healthcare, says Paul Savill, Senior Vice President of Product Services at tech company Lumen.
Many devices currently out there (for example health monitors, sensors and wearables) are either not connected, or are collecting a large amount of unprocessed data that needs to be stored in the cloud. As healthcare often deals with very sensitive information, this creates privacy and security concerns that require a lot of attention.
An edge on the hospital could process data locally, protecting data privacy and instantly alerting caregivers when unusual trends occur with a patient and help is required.
Also, robots assisting in surgery must be able to analyse data instantly to assist safely, quickly and accurately. If these devices rely on submitting data to the cloud and waiting for a response before making a decision, it could be fatal for the patient.
"We're not replacing doctors or care teams with this technology," explains Rich Bird. "We're helping them make quicker and better-informed clinical decisions by generating insights from providing data that helps improve the outcomes for their patients."
On the brink of a breakthrough?
With healthcare and autonomous vehicles, we are only scratching the surface. Smart cities, for example, aim to improve the quality of life for residents with smart parking, traffic management or improving security by proactively monitoring public spaces and law and order.
Likewise for the oil and gas industry; if there are any problems or unusual activity, this can be detected instantly. Edge computing allows us to analyse the data immediately, identify the cause of the issue and take the appropriate actions to rectify the situation long before significant damage occurs.
Even in the financial sector detection of fraudulent behaviour often happens post-event. Banks detect suspicious transactions and take steps to prevent further losses by freezing cards or accounts. Running AI-enabled analytics at the edge could detect fraudulent patterns and proactively prevent fraud — benefitting both the banks and their customers.
Let’s be clear, countless applications will leverage the possibilities offered by edge computing to create solutions that were previously deemed infeasible or even science fiction. As always, adoption will not happen overnight, but one step at a time, offering real-world improvements to already existing cloud solutions. The real question is: are you ready to start living on the edge?