Cloud computing has become a most used business jargon in the area of high-performance computing as it provides on-demand services over ashared pool of internet resources. Process scheduling is one of the most important research issues to be focused on improving the performance of a cloud-based queuing system. The process of scheduling is to assign an appropriate resource to the task to achieve one or more objectives. Nowadays, the scheduling of jobs in cloud leads to NP-hard problem due to its large solution space and longer time to find an optimal solution. To find an optimal solution for the above issues and to improve theperformance of execution, a new priority based scheduling algorithm Enhanced Priority Scheduling Algorithm (EPSA) is proposed. The EPSA algorithm prioritizes jobs based on the job attribute. The attribute of jobsis execution time, resource requirement, CPU utilization, and dependency and target time. These parametersare combined and formulated for priority calculation. The job priority measure is used to generate a fuzzy decision tree (FDT). The FDT predicts the ordering position and service acquiring time for jobs that enter the cloud-based queuing system. EPSA algorithm improves the execution time and shows better performance compared to existing scheduling algorithms. The Proposed algorithm is implemented using JSIM-graph of JMT for performance modeling and evaluation.