Presenting a model in smart electronic health networks based on IoT-Fog for health care to optimize resources

There have been huge improvements in healthcare delivery thanks to sensing and the Internet of Things (IoT). By utilizing cloud resources, the Internet of Things can broaden its reach. Contrarily, data gathered from healthcare IoTs can also help cloud improve its services. Because of the physical distance between the cloud and the Internet of Things, it is difficult to provide services that have special needs, such as low computational processing requirements or fast reaction times. Using the cuckoo optimization algorithm, this research introduces a novel approach to optimizing simulated e-health smart networks. The SHE-cuckoo optimization algorithm (SHE-COA) is the name of this specific approach. Cuckoo algorithm plays a crucial part in SHE-COA by assisting with the optimization of the search space size in order to attain the optimal solution. The outcomes of the current strategy were compared to those of the proposed one using the iFogSim application. When this study’s methodology is compared to earlier ones, the experimental results reveal a notable decrease in energy usage, network bandwidth utilization, and latency. In particular, the suggested method reduces latency by 41%, energy consumption by 38%, and network bandwidth utilization by 23%.