# A Survey from Real-Time to Near Real-Time Applications in Fog Computing Environments
## 2 Material and Methods
### Considerations  
We begin this section with the material, which consists of a description of the terms and approaches used in this article, that is, Edge Computing, Fog Computing, Real-time, and Near Real-time. We verified divergences in the concept of edge and fog computing. There is a group of researchers who understand that, in an IoT architecture, processing and communication are performed at the edge layer and, after that, the data are sent to the cloud for analysis. A second group considers the edge computing as a layer of devices with some processing and communication capacity. However, the edge layer sends the data to an intermediate layer, called fog computing, for the processing and presentation of the data, which will later send the results to the cloud computing for persistent storage. Fog computing, in turn, is conceptualized as an intermediate layer, between the edge and cloud computing layer that receives, transforms, processes, and presents the data to the user. Therefore, in this article, the authors consider that the IoT architecture is composed of the edge, fog, and cloud computing layers. In other words, we do not consider that the data processing is performed at the edge layer, and we consider that there is a need to have an intermediate layer to perform such role.  
In addition, we present three ways of conceptualizing real-time systems and we could see that there is also divergence in this conceptualization. Systems that make the best effort to perform their tasks are known as systems that respond near real-time. In view of this divergence of conceptualization of the real-time approach, we conducted an extensive search for articles in order to search for different concepts used to define real-time, which consists of the research methods used to develop our article.  
The research method consists of planning, conducting, and analyzing the selected articles. A research protocol was carried out with the objective of enabling the replication  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Application Type** & **Data Streaming** & **Faster Response** & **Fog Computing** & **Low Latency** & **Time, Delay or Latency Constraint** & **Total** \\ \hline Health & 1 & 2 & 13 & 2 & - & 18 \\ Smart Vehicular & 2 & 5 & 5 & 3 & 2 & 17 \\ Smart City & 2 & 3 & 6 & 2 & - & 13 \\ Scheduling Algorithm & - & - & - & - & 6 & 6 \\ Smart Home & - & - & 3 & 1 & - & 4 \\ Smart Things & - & 2 & 1 & - & 1 & 4 \\ Task Scheduling & - & - & - & - & 3 & 3 \\ Algorithm & - & - & - & 1 & 1 & 2 \\ Data Analytics & 2 & 1 & - & - & - & 3 \\ Face Recognition & - & - & 1 & 1 & - & 2 \\ Security & - & 1 & 1 & - & - & 2 \\ Smart Parking & - & 2 & - & - & - & 2 \\ Asset Tracking & - & - & 1 & - & - & 1 \\ Device-to-Device & - & - & - & 1 & - & 1 \\ Energy Save & - & 1 & - & - & - & 1 \\ Network & - & 1 & - & - & - & 1 \\ Protocol & - & - & - & 1 & - & 1 \\ Scheduling & - & - & - & - & 1 & 1 \\ Signal Anomalies & - & 1 & - & - & - & 1 \\ Smart Grid & - & - & 1 & - & - & 1 \\ Virtualization & 1 & - & - & - & - & 1 \\ IoT Applications & - & 1 & - & - & \(-\) & - \\ \hline Total & 8 & 20 & 38 & 13 & 16 & 95 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Publications separated by application and category.  
of the systematic review. After validating the protocol, a search was performed that returns 95 articles. These articles presented a pattern in the way real-time was defined, which allowed us to create a classification. This classification has five categories, as presented in this section. A brief description of the proposals for the selected articles is presented in the next section.