An Efficient Fog Layer Task Scheduling Algorithm for Multi-Tiered IoT Healthcare Systems

Abstract

IoT-based healthcare systems are becoming popular due to the extreme benefits patients, families, physicians, hospitals, and insurance companies are getting. Cloud is used traditionally for almost every IoT application, but cloud located far away from the devices resulted in an uncertain latency in providing services. At this point, fog computing emerged as the best alternative to provide such real-time services to delay-sensitive IoT applications. However, with the surge of patients, fog's limited resources may fail to handle the explosive growth in requests requiring advanced monitoring-based prioritization of tasks to meet the QoS requirements. To this end, in this paper, a level monitoring task scheduling (LMTS) algorithm is proposed for healthcare applications in fog to provide an immediate response to the delay-sensitive tasks with minimum delay and network usage. The proposed algorithm has been simulated using the Cloudsim simulator, and the results obtained demonstrated the efficacy of the proposed model.