## 4 Simulation Implementation
### Smart Office Building Floor Plan  
Figure 2 is an illustrative image of the floor plan, highlighting multiple IoT smart devices installed and strategically placed around this floor of the smart office building. Smart IoT devices such as CCTV cameras, CO\({}_{2}\) sensors, and lighting sensors are installed \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Devices** & **MIPS** & **RAM (GB)** & **Uplink (Mbps)** & **Downlink (Mbps)** \\ \hline Cloud Data Centre & 100,000 & 48 & 100 & 100,000 \\ Proxy Server & 10,000 & 16 & 100 & 10 \\ Fog Node & 7050 & 8 & 10 & 10 \\ CCTV & 2200 & 64 & 10 & 100 \\ CO\({}_{2}\) & 500 & 8 & 13 & 100 \\ Light Sensor & 100 & 4 & 13 & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Device configuration parameter values. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Parameter** & **Cloud** & \begin{tabular}{c} **Router/Proxy** \\ **Server** \\ \end{tabular} & \begin{tabular}{c} **Fog** \\ **Node** \\ \end{tabular} & \begin{tabular}{c} **CCTV** \\ **Cameras** \\ \end{tabular} & \
\begin{tabular}{c} **CO\({}_{2}\)** \\ **Sensor** \\ \end{tabular} &
\begin{tabular}{c} **Light** \\ **Sensors** \\ \end{tabular} \\ \hline Tier Level & 0 & 1 & 2 & 3 & 3 & 3 \\ CPU Speed & 100,000 & 10,000 & 7050 & 2200 & 500 & 100 \\ Internal RAM & 48 & 16 & 8 & 64 & 8 & 4 \\ Bandwidth & 100 & 100 & 10 & 10 & 13 & 13 \\ Uplink (Mbps) & & & & & \\ Bandwidth & 100,000 & 10 & 10 & 100 & 100 & 100 \\ (Mbps) & & & & & \\ Busy Power (w) & 16*103 & 107.339 & 100.339 & 12.95 & 1.6 & 9 \\ Idle Power (w) & 16*83.25 & 83.433 & 80.433 & 10 & 0.55 & 0.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Detailed network infrastructure and device configuration parameter values. in each office, meeting room, and other service areas. These smart IoT devices generate different types, sizes, and volumes of data. This section presents the floor plan of one floor, presenting the smart office building case study and the simulation output results. Figure 2 shows that this floor plan has 7 CCTV cameras, 17 CO\({}_{2}\) sensor devices, and 22 light sensor devices placed around the floor. Tables 4-6 display the simulation results of the smart IoT devices on this floor for both the Fog and Cloud computing scenarios. of energy consumption in a scalable scenario is that the energy consumption increases as the number of smart IoT devices increases, while energy savings can be achieved through decentralised computation processing in the Fog computing layer, eliminating the energy required to transmit data to the Cloud layer. In a real-world data centre, energy consumption typically consists of infrastructure data communication, power supply for backup systems, HVAC, and other environmental regulatory controls such as technological security controls, emergency fire controls, and temperature regulation systems. Energy consumption is essential as it affects the operational cost of infrastructure; therefore, this study is beneficial as it highlights some of the benefits of Fog computing, such as environmental protection and the availability, efficiency, and dependability of infrastructure devices, which aims to address the high energy consumption issue in Cloud computing [55]. According to [16], iFogSim2, microservices can be introduced to simulate the full potential of edgeward computation processing, moving away from the traditional monolithic architecture in Cloud computing. Microservices move seamlessly between the edge and Cloud, coordinating with each other to build applications through workload scalability and resource availability in the Fog computing layer.