Understand Edge Computing in 3 Minutes

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What is edge computing?

Edge computing is computing that’s done at (or as close as possible to) the source of the data, rather than the cloud routed through one of dozens of data centers to do all the work.

Why do we need edge computing?

The explosive growth of IoT devices has created unprecedented amounts of complex data which has

outpaced network and infrastructure capabilities. It is especially important for 5G networks.

What are the advantages of edge computing?

Speed – Computing at or near the source reduces latency

Security – Encrypting and storing information on the device keeps it out of the cloud

Bandwidth – Distributing workloads to the device reduces the overall amount of data traffic

Cost – Less data traveling across the network means less cost

What are the disadvantages of edge computing?

Increased attack surface – spreading the data to more devices creates more opportunities for malicious

attacks

More local hardware – devices may need to process data and require more powerful hardware

What are some examples of edge computing?

Autonomous vehicles – An autonomous vehicle needs to collect real-time for traffic lights, pedestrians, signs and traffic and process it locally to be able to react quick enough to avoid an accident.

Voice assistants – Voice enabled devices can separate the user’s voice from other surrounding sounds before submitting the request which allows for a faster response

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