# A Review of Edge Computing Technology and Its Applications in Power Systems
## 2 Review of Edge Computing Architectures
### Fog Computing  
The OpenFog Consortium Architecture Working Group [37] defined fog computing as a \"_horizontal, system-level architecture that distributes computing, storage, control and networking functions closer to the users along a cloud-to-thing continuum_\". Compared with other edge computing architectures, such as MAEC and Cloudlet computing, fog computing focuses on the communication and cooperation among decentralized devices, such as IoT devices. Thus, fog computing services are closer to the terminal devices and more efficient. This  
Figure 4: The overall hierarchical architecture of Cloudlet computing.  
primary feature can help provide quality and efficient services [38]. Fog computing usually involves a large number of ubiquitous devices. The service of fog computing can be accessed through connected devices at the edge. Therefore, the nodes of fog computing have high mobility, and the servers can be placed at the edge or any specified location.  
Fog computing is an expansion of classic cloud computing designed to address the challenges of latency and bandwidth. According to [PERSON] et al. [39], [PERSON] et al. [40], [PERSON] et al. [41], and [PERSON] et al. [42], the primary features of fog computing are low latency--since fog servers are close to the end devices, it also results in shorter response times; real-time interaction--fog computing services can response in a short time frame; wide physical distribution--compared to traditional cloud computing, fog servers can provide decentralized services in any location; real-time analytics--this involves collecting and acting on data as it is transferred to the fog nodes rather than sending it to a central point and waiting for processing. Fog nodes include lightweight computing units that handle small computing tasks. The central cloud servers only need to receive the essential data and complete complex computing tasks. Data processing becomes more efficient with less bandwidth usage and latency.  
Figure 5 shows an overall hierarchical architecture of fog computing. The bottom layer is closest to the end-user and is comprised of various end devices, such as IoT sensors, mobile phones, intelligent vehicles, and others, which are geographically distributed. These devices can sense and gather data from the physical environment and transmit it to the upper layer. The fog layer consists of a large number of fog nodes, such as routers and switches, which are responsible for data transmission, storage, and computation. Fog nodes can be installed in dedicated locations or on a moving carrier [43]. The computational ability of these fog nodes allows them to handle real-time analysis and provide service with low latency. Furthermore, the proximity of the fog layer to the terminal devices enhances communication efficiency. It connects with the cloud layer and delegates more complex and time-consuming tasks to the cloud center. The top layer comprises multiple powerful servers and storage devices. The cloud data center supports comprehensive computation and storage of a large amount of data. Tasks executed in this layer are usually complex and non-latency-sensitive. Nowadays, various commercial cloud services such as DigitalOcean, Apple iCloud, and Amazon EC2 are available [44].  
A large number of applications are developed by using fog computing architecture. We surveyed and summarized them as follows.  
Figure 5: The overall hierarchical architecture of fog computing.