In this insight, we look at what edge computing is, why it’s necessary, the benefits it delivers, and some examples of how it’s being used.
What Is It?
Edge computing is a computing architecture and distributed computing framework which means the computing and data storage is done near the source of the data. The idea is that it improves response times, gives faster insights, saves bandwidth, and doesn’t need remote servers (data centres and the cloud).
Why The Name ‘Edge’?
The ‘edge’ part of the name comes partly from the old edge servers for CDNs in the 90s that were deployed close to users, and the fact the computing happens near the source of the data – i.e. on the edge of a network and not at the data centre.
Why Is It Growing?
The massive and fast growth of the Internet of Things (IoT) has meant that the cloud, AI, and the network and infrastructure capabilities can’t effectively or efficiently manage the volume and complexity of the data that’s being produced by all the devices. Trying to send all that data to a main data centre of the cloud simply slows everything down (bandwidth and latency issues). Customers/users would also be frustrated by waiting and any real-time insights may suffer by a reliance on passing data backwards and forwards over a network to a cloud and data centre where there is a latency issue
Also, much of the vast amount data being produced is not being analysed and, therefore, isn’t providing insights that could help businesses to make savings or create new sources of competitive advantage or create new business opportunities. Edge computing can also help where a business has a need to personalise customer experiences, generate rapid insights and actions, and maintain continuous operations.
There could also be some environmental and sustainability benefits from reducing reliance on power-hungry data centres.
Edge Computing : Faster + Better Insights
Using an edge computing architecture (and mobile edge computing on 5G networks), therefore, can deliver faster response times and improved data analysis and insights, which may lead to happier customers and more potential business opportunities.
Challenges
Some of the challenges to edge computing are:
– Security issues, e.g. IoT devices can have poor security, so edge computing deployment must fully address security.
– Possible connectivity issues, e.g. poor, or erratic connectivity issues at the edge.
– Limited capability.
Examples of Edge Computing
Examples of where edge computing is used include:
– Remote monitoring and real-time analytics at oil and gas facilities, and mining companies getting more from their data through edge computing, helping to optimise operations and improve safety.
– Smart grids to help with energy consumption and the lowering of business costs.
– Farming – using sensors to help improve crops and yield.
– Patient-monitoring in hospitals.
– Network optimisation.
– Predictive maintenance, e.g. on manufacturing production lines.
– Traffic management.
– Gaming and content delivery, e.g. having edge servers close to gamers and caching content at the edge.
What Does This Mean For Your Business?
Edge computing can be a way to tackle several different issues for businesses, improve customer satisfaction and create new opportunities from better data insights. Deploying edge computing can help where certain operations need autonomy and personalised results, where real-time insights are essential, and can avoid any cloud security issues, as well as helping with data sovereignty. The widescale use of sensors, e.g. in manufacturing, facilities, vehicles, and more lends itself to edge computing, and with the number of IoT devices and the data sent from increasing all the time, edge computing is set to grow even more.
