## 2 Related Work
### Fog Computing Architecture
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Aspect:** & **Cloud** & **Fog** & **Edge** \\ \hline \multirow{3}{*}{Operator:} & \multirow{3}{*}{Cloud Providers} & Cloud and & \multirow{3}{*}{Edge Providers} \\  & & Network Access & \\  & & Providers & \\ \multirow{3}{*}{Architecture:} & \multirow{3}{*}{ Centralized} & Distributed & \multirow{3}{*}{Distributed} \\  & & Network & \\ \multirow{3}{*}{Basic equipment} & \multirow{3}{*}{Powerful servers} & equipment, & \multirow{3}{*}{Network} \\  & & dedicated & \\ \multirow{3}{*}{Basic equipment} & \multirow{3}{*}{Powerful servers} & computing nodes & \multirow{3}{*}{devierement, Edge} \\ \multirow{3}{*}{Energy consumption:} & High & Moderate & \\  & & & \\ \multirow{3}{*}{Latency:} & High & Moderate & Low \\ \multirow{3}{*}{User distance:} & Large & Relatively small & Very small \\ \multirow{3}{*}{Number of nodes:} & Small & Large & Very large \\ \multirow{3}{*}{Mobility support:} & Limited & Yes & Yes \\ \multirow{3}{*}{Security:} & Less (non-local) & High (local) & High (local) \\ \multirow{3}{*}{Response time:} & High & Low & Very low \\ \multirow{3}{*}{Computing power:} & High & Less power & Moderate \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison between Cloud, Fog, and Edge. Fog Computing Features  
The NIST [10] and the OpenFog consortium have identified several features that define Fog infrastructures, which are summarized below:  
* Proximity to end users and low latency: FC offers the advantage of being close to end users and having low latency. This is because Fog nodes are located close to end devices or data sources, allowing them to collect and process service requests, store the results at the Edge of the network, and send the responses to the service requester. As a result, Fog nodes (FNs) can reduce the amount of data transmitted across the network, minimizing the risk of data loss, thus minimizing the average response time. This feature renders FC well suited for delay-sensitive applications, such as live gaming traffic monitoring, among others. * Greater data control and privacy: Users have greater control over their data, thanks to the proximity of end devices with Fog nodes, rather than outsourcing them to distant Cloud data centers. In fact, FC enables data to be processed locally before transferring delay-tolerant data to remote servers [11]. * Heterogeneity: Fog nodes are available in a variety of form factors and will be deployed in a wide variety of environments [12]. In fact, the heterogeneity of FNs refers to the diversity of devices and configurations in which these nodes are deployed. That is, they exist in a multitude of sizes, shapes, and hardware capabilities. These nodes can be complete servers dedicated to gateways, specialized IoT devices, etc. What is more, these nodes are deployed in a wide variety of environments, ranging from dense urban to remote rural areas, from industrial plants to transportation infrastructures, etc. * Support for real-time applications: FC can support real-time applications thanks to its ability to have close proximity to end devices, enabling faster data analysis and response times than conventional centralized data centers. These include applications such as virtual reality, augmented reality, traffic monitoring, telesurgery, etc. [11]. * Decentralization and geo-distribution: Unlike the centralized architecture of Cloud computing, FC is a distributed architecture comprising huge, geographically distributed heterogeneous nodes covering numerous domains. This property enables location-based services and guarantees the provision of very low-latency services [11]. Figure 1: Fog Computing architecture illustrating the three tiers (Edge, Fog, and Cloud), where arrows represent the direction of data flow and interactions between the layers. * Autonomy and programmability: Fog infrastructures are characterized by autonomous decision making for the management of the applications deployed on it.