For the past five years we’ve all been talking about the cloud. It’s become all pervasive as companies move to consumption-based pricing, and we’ve watched the meteoric rise of the hyper-scalers like Amazon, Microsoft and Google. And that’s despite the cynic’s view that “the cloud is simply a data centre that nobody is supposed to know where it is”.

By Andy Rowland, head of customer innovation: energy, resources and manufacturing at BT

Currently, around 10% of enterprise-generated data is created and processed outside a traditional centralised data centre or cloud. By 2022, Gartner predicts this figure will reach 50%, with a great deal of interest in edge computing, where data is stored and processed very close to its point of consumption and/or creation; a factory, an oil rig, a retail outlet or even a container ship.

 

So why is this suddenly getting so much interest?

The main reason that companies are looking at edge computing is due to the sheer volume of data created by the Internet of Things and specifically Industry 4.0, where companies stream data from sensors to help them become more efficient. As an example, a typical oil rig contains 20 000 sensors – that’s a lot of data.

Using the cloud to process all this data poses a number of problems. Firstly, there is the matter of latency; can you really afford to send time or safety critical data all the way to the cloud for analysis and then back again to site? Then there is the cost of transporting all that data. And of course, there is security and regulatory compliance to consider.

 

How can edge computing help?

When dealing with a massive amount of data, having the ability to analyse and filter the data before sending it can lead to huge savings in network and computing resources.

Latency is reduced by reducing or eliminating the need for data transmission to and from core IT systems. Especially important for safety/time critical systems, this means that decisions can be made faster based on more granular and localized data. Edge computing can also mean reduced connectivity costs, decreased energy usage, less hardware and cables, less space required, lower installation costs and hardware maintenance and less set up time. And updates can be done remotely saving on travel costs.

Security and privacy risks can be reduced by limiting data flows between the point of collection and the core infrastructure, especially when those flows happen over the public internet. Using the edge helps you to adhere to in-country data protection laws. It keeps sensitive data within the device, anonymizing, analysing, and keeping the data at the source rather than sending identifiable information to the cloud.

 

What could this look like?

Edge computing is still in the ‘innovation trigger’ phase of its Gartner Hype Cycle, and it’s estimated to be another two to five years until it reaches maturity, but it will transform the way firms deploy and consume data centre resources. In the meantime, we are seeing customers start to adopt a three phased approach.

First of all, they are looking to consolidate various network related functions into a single box.  In the same way that we’ve seen convergence in the consumer space, so that we no longer need a separate camera, Sat Nav and alarm clock, just one smart phone, we are now seeing the same in networking and security.

Our customers are looking at edge devices that support virtual network functions (VNF) like routers, SD-WAN, acceleration and network optimisation. They’re also looking to consolidate security functions like virtual firewalls and privilege access management. And they want to have the ability to remotely install, configure and patch these devices.

Secondly, they are looking to add computing power to this box. The consolidated device now also needs to support containers and virtual machines to run different applications. By bringing the two together it helps to strengthen the business case for moving to the edge.

At our R&D labs, we’re building edge cloud compute platforms and applications to demonstrate the requirements and viability of the technology. We’re doing research and prototype work with key partners to understand things like customer and application requirements, technology maturity, the end-to-end architecture and orchestration required, as well as how to support the best interactions with customers, end users and other partners in the ecosystem. We’re also testing the technology and service wrap capabilities to achieve an integrated edge computing solution.

Finally, we are seeing customer keen to exploit the edge for more innovative applications.

Applications that we are exploring include:

  • Realtime video analytics such as object/ facial recognition;
  • Augmented/virtual reality applications for remote assistance or training purposes;
  • Automated remote control of vehicles, for example drones using 5G; and
  • Vehicle-to-vehicle and vehicle-to-infrastructure communications for things like collision detection.