As consumers and enterprise owners are just starting to warm up to the idea of cloud computing, another concept is sweeping the IT industry: edge computing. Not only does it have the potential to optimize basic and advanced data processing functionality, but the very foundation of edge computing is built on improving data storage and utilization on behalf of systems that rely on networks of any kind.
Cloud Computing Meets the Edge
Edge computing is often associated with cloud computing, but the two are not exclusive to one another. According to the popular research firm IDC, edge computing is a "mesh network of micro data centers that process or store critical data locally and push all received data to a central data center or cloud storage repository, in a footprint of less than 100 square feet."
In practice, the exact definition of edge computing might vary slight from the definition provided above. Basically, edge computing puts more processing power into the individual devices connected to a network. Instead of relying on a centralized server to the bulk – if not all – of the data processing, the load is relegated to the devices that are actually producing and using the data.
But the devices don't interact directly with the cloud servers – this would be haphazard and insecure at best. Instead, they're connected to programmable automation controllers – PACs – that handle all of the network communication needs.
To put it simply, any data that is processed or analyzed on the "edge" – or at the initial point-of-entry – of a network falls under the umbrella of edge computing. This is easily confused with fog computing, but the two actually describe two totally different processes.
Edge Computing Breaks Through the Fog
Fog computing is similar to edge computing in many ways. In a fog application, the brunt of the processing responsibility is still put on localized resources via a local area network, IoT gateway or fog node. In this scenario, which describes a typical fog network, uses a single – albeit incredibly powerful – processing device to transmit data to and from the cloud.
But the localized processing device doesn't have sole responsibility over the entire operation. If this were the case, a single catastrophe or incident would bring down an entire network. Individual devices still have some amount of processing responsibility, even within fog computing, to prevent such dire scenarios from occurring.
On the same token, it's easy to see why IT experts would prefer edge computing. Although a fog network often provides lower latency when transferring data to and from the cloud, it's more prone to failure than a typical edge setup.
Cloud Computing vs. Edge Computing vs. Fog Computing
There is a lot of confusion surrounding cloud computing and how it relates to the concepts of edge and fog computing. In a nutshell, both edge and fog computing are used to communicate with the cloud – or any other network – in order to send or receive data. Although they use different methods to accomplish this, their functionality and end-goals are often the exact same.
What is Edge Computing and How Does it Affect Data Storage?
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