How many times have you experienced high latency? Probably, at least several times during your life. This is often an issue with weak and unoptimized networks.
What is edge computing? Get the answer and learn how it helps with optimization to remove latency and network failure in the newest post by the Global Cloud Team.
In simple words, edge computing is an approach that helps developers make computing much faster. Instead of applying hundreds of processes and sending information to distant servers, devices can process data in local “nodes” such as a user’s computer. So, basically, it removes latency and makes things faster.
All processes are led to a network edge. This is where the device gets connected to the internet. Servers are usually distant from computers and other devices, while edge computing ensures there is something near them to speed up the connection.
One of the first versions was personal computing. Everything worked directly on the user’s device, and there were not many remote connections. All your software and data were accessible right from the PC.
Another version, cloud computing, became more popular recently. The major advantage it has is the possibility to increase storage and decrease its costs. This is when the servers are located distantly, and computers access them online.
Cloud computing comes with a disadvantage in the face of latency and network dependence. The reason is the distance and the type of connection. In the case of edge computing, it’s a little bit different. The length required for the information to travel is minimized. So, data is processed and transmitted to closer “nodes,” removing latency.
The simplest example of edge computing is a system of IoT cameras.
Primarily, these would be regular cameras that always stream video to a cloud server. Then, in the server, the data is transmitted to an application that detects motion only to save clips with activity. Information is always sent and relocated, meaning there are multiple “heavy” processes and huge latency.
If we apply edge computing, it will change the structure. First, the motion detection software will be in a local node. Second, the cameras will use an internal computer to run the application. Then, once the data is cut and edited, it would be sent to the cloud server.
As a result, we reduce bandwidth and latency. Also, the expenses for cloud servers are minimized because all it does is store information. Therefore, edge computing comes as a significant improvement for the whole system.
Edge computing has many ways of application with modern technologies. For example, its way of optimizing the whole network helps areas such as:
If you take a broad look at the topic, you’ll see that edge computing is a valuable addition to most industries. Its whole idea helps technologies work faster. Probably, that’s not the limit, and we’ll see an even better-optimized network in the near future.
Now, we shall cover the pros of edge computing:
Remember how many delays you’ve experienced because of a slow network? Well, edge computing is designed to bring this to an end.
Now, we shall cover the cons of edge computing:
So, as you can see, there aren’t that many drawbacks. The major issue would be money. Security and privacy is only a potential issue that can be minimized with a properly developed system.
Edge computing is truly a great way to optimize whole networks. It takes a tremendous effort to install it within your system, especially when there are no specialists with relevant knowledge.
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