A comparative analysis of different cloud computing method for scheduling healthcare tasks

The problem of efficient task scheduling in cloud-integrated, Internet of Things-based healthcare monitoring systems is examined in this work. We suggest Prioritized Sorted Task-Based Allocation (PSTBA), a novel scheduling method, to enhance task execution and boost system performance. In order to guarantee that vital healthcare monitoring tasks are finished on time, PSTBA ranks jobs according to their criticality, expected processing time (EPT), and virtual machine wait time. The process entails putting PSTBA into practice in an IoT cloud context and assessing its effectiveness using in-depth CloudSim simulations. The findings show that PSTBA works noticeably better than the current techniques, such as First-Come, First-Served (FCFS) and Sorted Task-Based Allocation (STBA) PSTBA specifically lowers the failure rate by 20% and 35.6%, raises the guarantee ratio by 2.5% and 4.8%, and decreases latency by 12.6% compared to STBA and 79.2% compared to FCFS. Moreover, PSTBA successfully reduces the number of key activities missed by 14.9% when compared to STBA and 51% when compared to FCFS. To sum up, PSTBA is a very successful scheduling method that improves job prioritizing and system stability for IoT-based healthcare systems.