A Cluster-Based Architecture for Fog Computing

As the number of Internet of Things (IoT) devices continues to grow rapidly, traditional cloud computing struggles to keep up—often causing delays, bottlenecks, and increased network traffic. To address these challenges, this paper introduces a cluster-based fog computing architecture designed to address the limitations of traditional cloud systems, such as high latency and network congestion, in IoT environments. By designing a distributing computational and storage resources closer to data sources, the proposed architecture aims to enhance scalability, reduce network messages, and improve service responsiveness across diverse domains. The study highlights the importance of flexible, efficient fog layer design to support real-time and latency-sensitive applications. The proposed architecture organized fog nodes using both physical and virtual servers, making the system more flexible, resilient, and capable of handling diverse scenarios. This approach focuses on reducing the number of messages sent across the network, which enhances speed and efficiency. The simulation results show the proposed architecture demonstrated a significant reduction in network congestion and latency, especially for time-critical applications. Overall, this work shows that this proposed architecture can improve the performance, reliability, and scalability of IoT systems—paving the way for smarter, faster, and more dependable IoT deployments in practice.