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What's the difference between fog computing and edge computing?

Fog computing and marginal computing are both concepts that were put forward in the early years, but why have they developed so much in recent years? Previously, the development of the Internet of things industry is not as rapid as it is now, and there are not so many devices in the Internet of things. In the past, the data was collected at the front end and calculated in the cloud transmitted through the network, and a series of data such as the calculation results were returned to the front end for corresponding operations. But what we are facing now is the access of huge Internet of things devices, and the amount of data generated every day has brought tremendous transmission pressure to the network. It is very unrealistic for TB-level operations to be transmitted to the cloud for real-time data interaction. Self-driving cars, for example, require lower network latency, which makes it necessary to shift computing power closer to the edge to improve the safety of its work. Based on this, fog computing and edge computing have been widely valued by everyone.

Fog computing and Edge Computing

Fog computing (Fog Computing)

This concept was pioneered by Cisco in 2011 as opposed to cloud computing. It is not a powerful server, but made up of weaker and more decentralized functional computers that infiltrate electrical appliances, factories, cars, streetlights and all kinds of objects in people's lives. To put it simply, it extends the concept of cloud computing (Cloud Computing), which is closer to where data is generated than cloud computing, where data, data-related processing and applications are concentrated on devices at the edge of the network, rather than almost all stored in the cloud.

Edge Computing (Edge Computing)

It further promotes the concept of "local area network processing power" in fog computing, but in fact, the concept of edge computing was put forward before fog computing. The origin of edge computing can be traced back to the 1990s, when Akamai launched the content delivery Network (CDN), which set up transport nodes close to end users, which can store cached static content, such as images and videos.

The processing power of edge computing is closer to the data source, and its applications are initiated on the edge side, resulting in faster network service response, which meets the basic needs of the industry in real-time business, application intelligence, security and privacy protection. Edge calculation is between the physical entity and the industrial connection, or at the end of the edge of the physical entity.

The whole system of edge computing consists of four key parts: intelligent devices (assets), industrial intelligent gateways: www.top-iot.com/, intelligent systems and intelligent services. It is a "bridge" connecting the physical world and the virtual world.

Similarities and differences between fog computing and Edge Computing

Both fog computing and Edge Computing Systems transfer data processing to the source of data generation; both try to reduce the amount of data sent to the cloud to reduce latency; and through the above strategies, both can improve system response time and security in remote critical applications because of the reduced need to send data over the public Internet and lower costs. Some applications may collect large amounts of data, which is expensive to send to a central cloud service. But only a small amount of the data they collect may be useful. If some processing is done at the edge of the network and only the relevant information is sent to the cloud, the cost can be effectively reduced.

For example, security cameras, sending 24-hour video to a central server will be very expensive, of which 23 hours may just be an empty corridor. If you use edge computing, do the corresponding edge calculation through the industrial intelligent gateway and send only the important data, you can choose to send only the hour when something actually happened. The price will be much lower.

Take vacuum cleaners as an example, centralized fog nodes (or IoT gateways) continue to collect information from sensors in the home and activate the vacuum cleaner if garbage is detected. In the solution of edge computing, the sensor determines whether there is garbage or not to send a signal to start the vacuum cleaner.

Both fog computing and edge computing involve processing data closer to the origin. The key difference is to deal with the exact location where it happened.

Fog computing is used differently from edge computing.

We can see that the two technologies are very similar. The fog computing process takes place on a local area network (LAN)-level network architecture, using a centralized system that interacts with intelligent gateways and embedded computer systems. Most of the data processed by edge computing comes from the device itself of the Internet of things.

According to a recent report by Million Insights, the global market for marginal computing is expected to reach about $3.24 billion by 2025. With the continuous development of the Internet of things and the production of more massive data, it is imperative to deal with the data close to the generation point.

Although there are some similarities between fog computing and edge computing, the methods of data collection, processing and communication are indeed different. All have their own advantages, fog computing and edge computing will play a very important role in the future Internet of things industry.

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