What is edge computing and what are the differences between edge computing and cloud computing?

Have you ever come across the term “Edge Computing” but had a slight idea about what is that all about, or you might have knowledge regarding edge computing but you are confused about the differences between it and cloud computing? This article will explain what is edge computing and the differences between edge computing and cloud computing in a straightforward manner.

So, what is edge computing? Well, edge computing refers to data processing and storage near the edge — the source of the data, instead of relying on the cloud which could be far away from the edge. An analogy to octopus might help you have a better understanding of edge computing. There are about 500 million neurons in an octopus’s body and the majority of neurons are found in its arms. Each arm can independently taste and feel the things around it and control some basic motions without input from the brain. The edge and cloud in the distributed network are like the arm and the brain of an octopus respectively, the independent activities happening at each arm is similar to the data processing close to the edge.

The diagram above shows how IoT (Internet of Things), edge computing, and cloud interact with each other. Before the emergence of edge computing, IoT devices, which could be a monitor or sensor, communicate with the cloud directly by sending generated data, and receiving computed data from the cloud. However, with the rapid development in IoT devices, latency became one of the major issues in the distributed network due to the enormous amount of data generated during the course of their operations. Imagine there are hundreds of IoT devices sending data to the cloud at the same time and wait for the cloud to complete the computation, the server on the cloud might be overloaded and performances of the IoT devices tend to be compromised. In the light of speed, computing edge came to help solve the latency issue. Instead of sending all the data and leaving all the computational tasks to the cloud, some of the data processing is done and stored near or on the IoT devices so that IoT devices are able to perform some operations without communicating with the cloud and the performances are significantly enhanced.

Improvements in the performances of IoT devices by moving the data processing and storage near the edge is not the only reason for increasing the speed of data processing. Even though the cloud the computationally powerful enough to handle an enormous amount of data at the same time, some applications or devices require real-time data processing by suffering nearly zero latency. Take self-driving cars as an example, real-time data processing is critical for their operations as any latency of data processing might lead to serious consequences.

Speed is just one of the cool benefits of edge computing, besides the benefit of speed, security is another essential benefit brought by edge computing since local data process prevents data from being disrupted by cyber-attacks through the way to the cloud. Another benefit of edge computing is cost. Local data processing and storage significantly reduce the bandwidth needed to communicate with the cloud, thus less cost is required to maintain the entire network as well as the operations of the IoT devices and the cloud.

In conclusion, this article is conveying the message that edge computing is better than cloud computing. In fact, edge computing and cloud computing are both critical components in the distributed network. The development of edge computing is to resolve some of the drawbacks of cloud computing and to increase the robustness of the distributed network.