Abstract
Healthcare applications, such as remote patient monitoring systems (RPMSs), utilize various Internet of Things (IoT) devices, including headsets, pulse oximeters, EEG monitors, ECG monitors, and smartwatches, to remotely gather critical patient data, such as heart rate, body temperature, and blood pressure. This technology enables healthcare professionals to collect patient information without needing in-person visits, streamlining data collection. Once the data is collected, these IoT devices transmit the information to smartphones, which serve as edge devices. Given the limited processing capabilities of smartphones, data preprocessing is necessary before transferring the data to the fog layer, where it can be analyzed using advanced algorithms to generate treatment recommendations and alerts. However, when the fog nodes overload, the computational tasks may need to be shifted to the cloud, which can impact the quality of service (QoS), especially in situations where patients require immediate attention. To maintain high levels of user satisfaction and ensure QoS, efficient fog resource management is crucial. This includes the reduction of job response time and cloud service dependency, optimization of the network utilization, and moderation of service cost. Currently, conventional methods using cloud computing or the brute force algorithm (BFA) fail to meet the desired QoS standards. This study involved the simulation of an IoT setting for resource management using the Sparrow Search Algorithm (SSA) and its comparison with both the BFA and Particle Swarm Optimization (PSO). The results indicate that compared to the BFA, the SSA enhances the response time by 20% and provides better resource load balancing. Additionally, compared to PSO, the SSA demonstrated a 10% reduction in network usage and improved efficiency in fog resource utilization.
Keywords
IoT, edge–fog–cloud computing, Sparrow Search Algorithm SSA, particle swarm optimization PSO, breath first algorithm BFA
Article Type
Article
First Page
52
Last Page
62
Publication Date
4-30-2025
Recommended Citation
Alkayal, Entisar and Alharbi, Nesreen M.
(2025)
"IoT Resource Management Based on the Sparrow Search Algorithm in Healthcare Applications,"
Journal of King Abdulaziz University: Computing and Information Technology Sciences: Vol. 14:
Iss.
1, Article 5.
DOI: https://doi.org/10.64064/1658-6336.1005