# A Study on the Design of Fog Computing Architecture Using Sensor Networks
## 2 Related Research
### Fog Computing  
Edge computing is a concept that contrasts with cloud computing. Cloud computing is a way to communicate directly with a central data center, whereas edge computing communicates primarily with the so-called \"edge data center,\" which is located near the device, and leaves secondary work to the central cloud. In other words, edge computing is a computing topology concept.  
Fog computing was first proposed by CISCO in January 2014. [PERSON], senior director of corporate strategy innovation at CISCO, has stated that edge computing is a component or subset of fog computing. He said: \"fog computing seems to be a way to handle where data is generated from where it is stored. Edge computing is simply to be processed near the point where the data was generated. Fog computing includes not only its edge processing but also the network connections necessary to import that data from the edge to the endpoint\". Fog computing refers to the network  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Layer** & **Name** & **Detailed Role** \\ \hline
1 & Physical Devices \& Controllers & The “Things” in IoT \\
2 & Connectivity & Communication, Processing Units \\
3 & Fog Computing & Data Element Analysis, Transformation \\
4 & Data Accumulation & Storage \\
5 & Data Abstraction & Aggregation, access \\
6 & Application & Reporting, Analytics, Control \\
7 & Collaboration \& Processes & Involving People, Business Processes \\ \hline \hline \end{tabular}
\end{table}
Table 1: CISCO’s Internet of Things Reference Model.  
Figure 2: Concept of the Internet of Things.  
connections between edge devices and the cloud. On the other hand, edge computing refers more specifically to computing processes performed near edge devices. Therefore, fog computing includes edge computing, as well as networks that are required to send processed data to the final destination. In other words, it is a standard that defines how edge computing should work. It creates a rapid control loop, using a fog computing model, because data is processed at the device [9].  
The structure of fog computing is shown in Figure 3.  
Fog computing [9; 10; 11] is a virtual platform that provides processing, saving and networking service between a device and a cloud computing data center. However, it is not exclusively located at the edge of network. Processing, saving and networking resources are building blocks of cloud and fog.  
The cloud layer, which is the core of fog computing, performs data virtualization, analysis, machine learning, and updates rules and patterns in the fog layer's proxies. The proxy server serves as a simpler cloud server. A concentrated data storage provides creditability and easy access to data by computing resources in a cloud. A data storage that is located at the center of the fog computing structure can be accessed by both device layer and fog layer [12]. The fog computing structure provides some advantages as follows:  
* Reduced network load: In the fog computing structure, the amount of data flowing into a network is reduced because computation is conducted at a network edge near IoT devices.
* Mobility support as a default function: The Mobility according to reliability is a fundamental requirement to many IoT applications. The device resources like smart phones and laptops may provide physical or virtual mobility to support a mobile IoT application.
* Context awareness: In the fog computing structure, resources provide context awareness relating to data created by a sensor. The device resources play roles in combining data at a sensor, using position or application context.
* No single defective point: As calculation is completed in a distributed way in fog computing, the model does not have a single defective point. Several snapshots of an application can be allocated at a cloud to improve reliability.