January 28, 2018

An introduction to Edge Computing

Ilja Postel

Gartner named Edge Computing one of the tech-trends to watch out for in 2018. But what is it, and why does it matter? In this article, we’ll provide you with an introduction.

what is edge computing

Edge Computing: what is it?

Cloud computing changed the way we work, because it transfers large parts of our data –as the name may suggest– to the cloud. In a normal case, a business will use a cloud provider to facilitate their storage on the cloud. In turn, these providers will build big data centers, which allows them to scale up and keep their services affordable. A side effect: most of our data stored in ‘the cloud’ needs to be transported to this cloud, that’s geographically far from its user.

In most cases this isn’t problematic: transportation of this data goes very fast. But what do we do in cases where time is of the essence, and every nanosecond matters? Or cases where IoT devices experience connectivity problems? This is where edge computing can help us out, because less communication bandwidth is needed to communicate between sensors part of the Internet of Things and the cloud.

The main idea behind edge computing is to process data as closely to the source as possible. For instance, in a mini data-center or another intelligent machine with some processing power. Rather than sending all data collected by IoT sensors directly to the cloud, it processes this data within the network, and only relevant data, or information data conveniently bundled, is sent.

After a wave of digitalization and centralization, edge computing fulfills the need for decentralization, because the centralized model doesn’t fit all IoT infrastructures.

Elements of Edge Computing

Edge computing is a vague term: when is something ‘mere’ cloud computing, and when can we speak of an edge computing network? Although it is still a fairly new trend and its usages and benefits are not entirely defined yet, these five elements expand on the what’s and why’s of edge computing.

  • Proximity is in the edge: communication is more efficient when devices are near to each other. Speed of reaction improves when devices are near, which can make a network run more efficiently.
  • Intelligence in the edge: it’s important to have intelligent devices in ‘the edge’, as this enables them to take autonomous decisions on what data is passed on to the cloud, reducing the needed communication bandwidth.
  • Trust is in the edge: like in any type of computing, cyber security is an essential element. Edge computing introduces new security challenges, and we need to face those challenges.
  • Control is in the edge; devices in the network need to be in control. For instance, tasks on what data to send and what data to process and locally store need to be assigned to local devices in the network.
  • Humans are in the edge; like in any network – we are still a part of it. In the end, information is still meant for human actors, so they should have final control.

edge computing

Why does it matter?

There are three main motivators for using edge computing.

First, there’s the issue of privacy: sensitive data can be processed on-site. Sending data to an external cloud introduces new privacy risks regardless of how well-secured the connection is, and processing this data locally can solve some of the privacy issues you may encounter otherwise.

Secondly, there’s latency. In cases where speed of reaction matters, edge computing can be a useful addition to cloud computing. Rather than transporting data directly to the cloud, in a network using edge computing it will be processed within the network, and only relevant information will be transported from the edge of the network to the cloud.

Finally, it avoids connectivity issues, as it requires less connectivity from the IoT sensors. For instance, rather than having to be connected to a central cloud, an IoT device can be connected to a computer or device ‘on the edge of the network’, which in practice means within the same room or same building – rather than geographically far away.

Examples of Edge Computing

Edge computing collects and processes data within a network rather than sending everything to a cloud immediately.

For instance: imagine that you have a smart fridge that sends out information about its temperature. Rather than constantly sending out its temperature in real-time, it could send out temperature information in short intervals, only sending out notifications directly if temperatures get too high or too low.

Another example is the usage of IoT devices in health care. Time can be of the essence – and reacting to abnormalities too late can -quite literally- cost lives. Processing data in small, on-site data centers leads to faster reactions, for instance by adjusting dosage of an automatically administered drug, or alerting medical staff about the abnormalities measured.

The Intelligent Digital Mesh

Gartner proclaimed 2018 the year of the intelligent digital mesh, which is an “entwining of people, devices, content and services”. In practice, this means that systems are becoming more intelligent and autonomous using AI in nearly every technology, combining both the digital and real world to create an interconnected environment.

Combined with cloud computing, edge computing enables a powerful and efficient system, and for this reason Gartner identified Edge Computing as one of the tech trends of 2018.

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Topics: Digitalization, Internet of Things, edge computing, cloud computing