What is Edge Computing?

by Richard Jones, 4 May 2019

What is it?

Gartner defines edge computing as – ‘a part of a distributed computing topology in which information processing is located close to the edge – where things and people produce or consume that information.’

At a really basic level, edge computing brings the processing and storage of data closer to the device that are gathering and using data instead of sending this information miles away to a central location. This is done so that there is little effect on the data or the applications process due to latency. Also companies can save money by doing the computing locally.

IOT (Internet of Things) is the main reason for the growth of edge computing. The devices which connect to the internet for receiving and sending information from the cloud generate huge amounts of data in the course of their operation. These devices can really suffer due to latency but also the costs in bandwidth can be tremendous.

Edge-computing hardware and services help solve this problem by being a local source of processing and storage for many of these systems. An edge gateway, for example, can process data from an edge device, and then send only the relevant data back through the cloud, reducing bandwidth needs. Or it can send data back to the edge device in the case of real-time application needs.

Why Does Edge Computing Matter?

For many companies, the cost savings alone can be a driver towards deploying an edge-computing architecture.

Companies that embraced the cloud for many of their applications may have discovered that the costs in bandwidth were higher than they expected.

Companies such as NVIDIA have recognised the need for more processing at the edge, which is why we’re seeing new system modules that include artificial intelligence functionality built into them. The company’s latest Jetson Xavier Module for example, is smaller than a credit-card, and can be built into smaller devices such as drones, robots and medical devices. Artificial Intelligence (AI) algorithms require large amounts of processing power, which is why most of them run via cloud services. The growth of AI chip-sets that can handle processing at the edge will allow for better real-time responses within applications that need instant computing.

How can we help?

Indectron can help when deploying edge computing infrastructure, with points of presence throughout the UK you can be assured that wherever your ‘Edge’ is we can get the latency and processing down to a minimum for you to enable your applications to run smoothly and quickly.

Speak to us to find out how we can help.

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