As the trend of the Internet of Everything continues to deepen, the number of end devices such as smart phones and smart glasses has continued to increase, making the growth rate of data far exceed the growth rate of network bandwidth; at the same time, many new applications such as augmented reality and unmanned driving are increasing. The emergence of higher requirements for delay. Edge computing combines computing, network, and storage resources at the edge of the network into a unified platform to provide users with services, so that data can be processed in a timely and effective manner near the source. This model is different from cloud computing, which must transmit all data to the data center, bypassing the bottleneck of network bandwidth and delay, and has attracted widespread attention.

How to understand edge computing

In recent years, the rapid development of big data, cloud computing, and smart technology has brought profound changes to the Internet industry, and has also put forward new requirements for computing models. In the era of big data, the amount of data generated every day is increasing rapidly, while the data in the context of applications such as the Internet of Things is geographically dispersed, and higher requirements for response time and security are put forward. Although cloud computing provides an efficient computing platform for big data processing, the current growth rate of network bandwidth is far behind the growth rate of data. The decline of network bandwidth costs is much slower than the decline of hardware resource costs such as CPU and memory. At the same time, the complex network environment makes it difficult to achieve a breakthrough increase in network latency. Therefore, the traditional cloud computing model needs to solve the two major bottlenecks of bandwidth and latency. In this application context, edge computing emerged as the times require, and has received extensive attention from researchers in the past two years.

The edge in edge computing refers to the computing and storage resources on the edge of the network. The edge of the network here is opposite to the data center, and it is closer to users in terms of geographic distance or network distance. Edge computing is a technology that uses these resources to provide services to users at the edge of the network, so that applications can process data near the data source. If we understand edge computing from the perspective of bionics, we can make this analogy: cloud computing is equivalent to the human brain, and edge computing is equivalent to the human nerve terminal. When a needle punctures the hand, it always closes the hand subconsciously, and then the brain realizes that the needle punctures the hand, because the process of retracting the hand is an unconditioned reflex directly processed by the nerve terminal. This unconditioned reflex speeds up people's reaction speed, avoids greater harm, and at the same time allows the brain to focus on processing advanced intelligence. The future is the era of the Internet of Everything. Cisco predicts that 50 billion devices will be connected to the Internet in 2020. It is impossible for us to make cloud computing the 'brain' of every device. Edge computing is to let devices have their own 'brains.'

In order to make it easier for everyone to understand, we can think of a very magical creature in the world-octopus. As an animal with the highest IQ among invertebrates, octopus has a huge number of neurons, but 60% are distributed in octopus. Eight, on one leg (wrist and foot), the brain is only 40%. Escape and hunt very quickly, the eight legs are clear, never entangled and knotted, thanks to the octopus's 'multiple cerebellums + one brain' similar to distributed computing.