Efficient Resource Management for Latency Optimization in Fog-Based Smart Farming

The integration of Internet of Things (IoT) solutions in agriculture has revolutionized the industry, giving rise to the emergence of IoT-driven smart farming. Additionally, fog computing, an extension of cloud computing, offers computing, storage, and networking services to latency-sensitive applications in smart farming, including agricultural robots (Agribots), anti-hail systems, and plant disease monitoring systems. However, efficiently placing application modules on fog nodes is often a challenge when implementing fog computing in IoT applications. Due to the limited resources (RAM, CPU, and bandwidth) of fog nodes, only a constrained number of modules can be operated simultaneously on these fog nodes. Thus, ensuring optimal placement is essential to balance the workload across fog nodes, ultimately meeting the performance requirements of latency-sensitive applications. Therefore, this paper introduces a module placement scheme designed for fog-based smart farming systems, aiming to minimize latency, optimize bandwidth (network usage), and reduce energy consumption. To assess the effectiveness of the proposed algorithm, we conducted simulations using iFogSim under two distinct scenarios with varying topologies. The obtained simulation results demonstrate that the proposed scheme effectively optimizes resource utilization, minimizes latency and optimizes network usage.