FORCE: Optimal Resource Utilization Framework for Fog-enabled Green Communication in IoMT

The Internet of Medical Things (IoMT) has revolutionized healthcare by integrating smart devices to monitor, analyze, and optimize patient care. Various healthcare devices generate a large volume of data daily, which uses a lot of storage and bandwidth. Fog computing is a promising paradigm that extends cloud computing capabilities near the network edge, allowing for real-time processing of healthcare data. In a fog-enabled IoMT environment, effective load balancing is essential to maximize resource utilization and guarantee timely and reliable healthcare services. This paper presents a load-balancing framework, i.e., FORCE, especially for fog-enabled IoMT environments. The FORCE focuses on challenges present in healthcare applications, such as meeting low latency requirements and dynamic workloads, and thus accelerates the idea of faster communication between the end devices, or IoT wearables, and fog nodes. To provide low-latency processing, the framework considers the fog computing architecture and brings computation close to healthcare devices. The FORCE delivers healthcare services with reduced latency and energy consumption. For the scenario wherein the region attribute is used to determine the optimal node result, the time to compute that was obtained is 14.82 seconds. In contrast, the computation time in later scenarios without considering region attributes is $\mathbf{7 6. 8 9}$ seconds. Hence, the FORCE efficiently reduces the searching time for finding the optimal node. Based on the simulation results, it can be concluded that the FORCE effectively optimizes both latency and energy consumption.