Edge Computing and Why It Should Matter to You
Edge computing is changing the way data as we know it is being processed and distributed to and from millions of devices around the world. The rapid growth of internet-connected devices over the past decades as well as new applications that demand real-time computing power, is the drive that pushes edge-computing systems to where they are today. With 4G LTE starting to become a thing of yesteryear, faster networking technologies such as 5G, are letting edge computing systems fast-track the creation and support of real-time requests, such as instant analytics, self-driving automotive, and AI. At the beginning, the goal of edge computing was to lower the costs of data traveling long distances due to the growth of data. However, it is the rise of real-time applications that need processing at the edge that will continue to drive edge computing into the future.
What is edge computing?
Edge computing is defined 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. A simpler way to explain edge computing is running less processes in the cloud and moving them to local machines like a computer, smart device, or server. Bringing computing to the networks edge reduces the long-distance communication that is required.
Edge computing brings data processing and data storage closer to the devices that are generating the data, instead of depending on a server in a distant area. The end user benefits from the fact that applications relying on real-time data avoids latency issues that can affect performance. Edge computing was really developed solely because of the explosive growth of smart devices in the last decade.
While a single device producing data can transfer it across a single network quite easily, problems arise when multiple devices transmitting data at the same time increases. Not only will quality suffer due to time it takes to transfer data, but the costs in increased bandwidth can be monstrous. Edge-computing helps solve this latency issue by being a local source of data processing and storage. An edge gateway, processes data from an edge device and sends only the relevant data back through the cloud, reducing bandwidth.
Quite the opposite of edge computing, these data centers are under the sea
Why does edge computing matter?
The budgetary savings alone can be a key motivator for most organizations to implement edge-computing. Businesses that incorporated the cloud for many of their applications could start to notice the costs in bandwidth were higher than they originally thought.
However, the ability to process and store data faster appears to be the greatest benefit of edge computing. It allows for organizations to enable more efficient real-time applications that are critical to companies. Applications similar to VR and AR, autonomous cars, the emergence of smart cities and building-automation systems require an immediate processing and response.
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How is edge computing different from other types of computing?
If you can think back to the first computers, they were giant CRT monitors that could only be accessed directly or via terminals that were basically an extension of the computer. With the development of PCs, it allowed computing to take place in a much more personal way. Personal computing was the principal computing model for a number of years.
A more recent innovation, cloud computing, offers several benefits over on-site computing. Cloud storage is centralized in a vendor-managed collection of data centers that can be retrieved from any device over the Internet.
However, a disadvantage to cloud computing can be latency due to the distance between users and the data centers where the data is stored. Edge computing shifts computing closer to end users to minimalize the distance that data has to travel, while still keeping the same aspect of cloud computing.
