Shulou(Shulou.com)06/03 Report--

With the Internet of Things becoming more and more popular, and accompanied by the Internet of Things, there are various concepts and technologies, one of which is edge computing. In the small classes of the first two periods, Xiaobian talked to you about fog computing and haze computing. I wonder if you still have an impression.

In fact, edge computing and fog computing are similar, fog computing is only relative to cloud computing. It's just called marginal calculation. It's higher.

The following small series gives you a popular talk about edge calculation.

Why do you want to speak in plain language? I'm afraid that if it's not plain, you won't understand. When new things come out, they often need a process of acceptance and understanding. Just like when the Internet first came out, many people didn't know about the Internet, so they had to popularize science slowly so that everyone could accept and understand it slowly. Who explains what the internet is now?

Edge computing has also been around for some time, but with the development of the Internet of Things, the concept of edge computing has also begun to become popular. Let's start with a non-trivial introduction to the concept of edge computing:

Edge computing is a decentralized computing architecture. In this architecture, applications, data, and service computations are moved from the central node to the logical edge nodes of the network.

In other words, edge computing breaks down large services that are handled entirely by central nodes into smaller and more manageable parts that are distributed to edge nodes. Edge nodes are closer to user terminals, speeding up data processing and transmission and reducing latency.

The above is an explanation of edge computing extracted from a web article by Xiaobian. The whole explanation is basically technical terms, most of them read this paragraph, still do not understand what is marginal calculation.

First of all, let me give you an inappropriate example. For example, there is an APP, when users use this APP, they will collect user information, such as collecting the user's age, gender, mobile phone number, address location, search history and other information, and collecting this information is mainly to better analyze the user's behavior and interested things, such as cars, houses, books, food and other interested things. and deliver content and advertising more accurately.

This is a very common function, but it is such a function, how to hook up with edge calculation? Before edge computing, it was cloud computing.

If you are using cloud computing, the behavior of this APP is like this:

After the APP collects the information, it uploads all the basic information to the server, and then the server executes the algorithm to calculate and identify the user's interests and hobbies, and may even calculate the user's consumption ability. The server can then deliver content and advertisements of interest to the user based on the calculated results.

If edge computing is used, the APP behaves like this:

After the APP collects the information, it does not upload it to the server. Then APP itself calculates and identifies the interests and hobbies of this user, and can also calculate the consumption ability of this user, that is, the computing function of the server, which is directly completed by APP. Then the server only needs to ask the APP which user is likely to make millions a year and which user is single. APP only needs to tell the server that this daodao user is handsome, single, likes to travel, writes poetry, and can put dating beauty content for him.

In this way, there is no server involved in the calculation, and the server is not involved in collecting information. Because this information is collected and calculated in the APP itself, it is not uploaded, so it does not involve information collection.

This is edge computing.

That is, the part previously calculated by the server is now directly calculated by the information collection equipment, and then the calculation result is directly output to the server. The server only needs the results, not the process data.

So, what is edge computing?

Edge computing, to put it bluntly, is (server) cloud computing too lazy to calculate, on this data, you in the data collection, by the way, calculate yourself, everything thrown to the server to calculate, very tired. And so, edge computing comes. What are the advantages of edge computing?

1. Get the moon first near the water tower

Edge computing is distributed and close to the device side, so it can better support real-time processing and execution of local services.

2. Simple, not rude and efficient

Things at home do not bother cloud computing far away. Edge computing directly filters and analyzes the data of terminal devices, saving energy, time and efficiency.

3. Save worry and effort and save flow

Edge computing mitigates data explosion and network traffic, using edge nodes for data processing and reducing data traffic from devices to the cloud.

4, intelligent and more energy-saving

The edge computing of AI+ edge computing combination is not only computing, but also intelligent. In addition, the combination of cloud computing and edge computing costs only 39% of cloud computing alone.

Since edge computing is so awesome, can cloud computing be replaced?

Although more and more basic tasks will be handed over to edge computing in the future, this can only mean that the devices and equipment where the edge is located will become more and more sensitive, but it cannot be said directly that these tasks have nothing to do with the cloud. They are a kind of existence that makes each other more perfect.

Edge computing and cloud computing work in synergy with each other, they are complementary to each other, and together enable the digital transformation of the industry. Cloud computing is an orchestrator responsible for big data analysis of long-cycle data, capable of operating in areas such as periodic maintenance and business decisions. Edge computing focuses on real-time, short-cycle data analysis to better support local business timely processing execution. Edge computing is close to the device end and also contributes to cloud data collection, supporting big data analysis of cloud applications. Cloud computing also outputs business rules to the edge through big data analysis for execution and optimization.

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