# Energy-Efficient Distributed Edge Computing to Assist Dense Internet of Things
## 3 Proposed Distributed Edge-Based IoT Structure  
The proposed model has five main tiers. Figure 1 presents the simplified architecture of the proposed distributed edge-based IoT network. Table 1 presents the description and specifications of the proposed system main layers. IoT devices generate data and perform initial computational tasks. Depending on network conditions and energy considerations, they can offload tasks to nearby fog nodes or MEC servers. Fog nodes act as intermediaries, processing and aggregating data from multiple IoT devices. They can further offload tasks to MEC servers if additional processing power is needed. MEC servers provide high computational power for more complex tasks and real-time analytics. They also manage task distribution and load balancing across the network. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Layer** & **Description** & **Deployed Devices** & **Functions** \\ \hline Layer (1): L\({}_{1}\) & Perception layer/data generation layer & End devices, IoT nodes, sensors, actuators, and other devices generating data & \(\bullet\) & Devices generate data and workloads of computing tasks related to different applications and services. \\ \hline Layer (2): L\({}_{2}\) & First distributed edge computing layer/data processing layer (1 st-layer processing) & Fog nodes distributed throughout the network & \(\bullet\) & They perform initial processing and can offload tasks to nearby fog nodes or MEC servers. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Description of the main layers of the proposed IoT structure. Figure 1: The architecture of the proposed edge-based IoT network. The proposed system structure combines MEC and fog computing to develop a reliable, scalable, and energy-efficient network for IoT applications. Fog computing alone cannot meet the demands of dense IoT networks, because fog devices have limited resources. Due to their size and mobility, market-available fog nodes have limited processing and computing capabilities. Conversely, MEC nodes, while offering substantial computational power, are stationary and cannot address scenarios requiring mobility or distributed processing closer to highly-dynamic IoT devices. The proposed architecture leverages the complementary strengths of fog and MEC nodes. Fog nodes provide localized mobile processing for latency-sensitive tasks, while MEC nodes handle resource-intensive operations requiring high computational power. This hybrid approach ensures scalability, mobility support, and efficient resource utilization, particularly in dense IoT deployments. MEC servers are placed at the network edge, i.e., access network, close to the end users. The deployed MEC handles real-time data processing and analytics and provides low-latency responses for time-sensitive IoT applications. These edge devices also offload tasks from the core network, reducing congestion and improving performance. Fog nodes are distributed throughout the network, positioned between IoT devices and MEC servers. The proposed structure depends on fog nodes as an additional edge computing layer to assist dense deployment. Fog nodes are deployed to provide intermediate processing capabilities and aggregate and preprocess data from IoT devices before forwarding them to MEC servers. Also, the deployed fog nodes handle tasks that require moderate latency and computational power. Tasks are offloaded based on a decision making algorithm that considers factors like task complexity, node energy levels, and network latency. IoT devices offload simpler tasks to fog nodes, while more complex tasks are sent to MEC servers. Fog nodes can further offload tasks to MEC servers if their computational resources are insufficient. The second and third layers of the system represent the distributed edge computing layer, which comprises both fog and MEC units. The network has a hybrid computing model organized, hierarchically.