Research on Priority-Based Task Scheduling in Cloud Computing focuses on developing methods that efficiently allocate resources while respecting task priorities to improve overall system performance. Recent studies highlight heuristic approaches using models like M/M/n queuing to optimize task execution, dynamic priority-based scheduling for edge and healthcare applications to handle real-time data and resource management, and multi-objective strategies in fog computing that optimize makespan, energy consumption, execution cost, and reliability. These advancements collectively enhance resource utilization, ensure timely completion of high-priority tasks, and support application-specific requirements in cloud, edge, and fog computing environments.