Cloud computing is an emerging trends in distributed computing which offers pay per model as user demand and constraint. Cloud applications having variety of composition, configuration, and deployment supplies. To quantify the performance of resource allocation policies and application scheduling algorithms at finer details in Cloud computing environments for different application and service modules under varying load, energy performance. system size is a challenging problem to tackle Cloud consist of a group of virtual machine which includes both computational and storage space facility. The primary aim of cloud computing is to provide better resourceful access. Cloud computing is based on the concept of distributed computing, grid computing, and virtualization techniques. Cloud is developing day by day and faces a lot of challenges, one of them is scheduling. Scheduling refers to a set of policies to control the order of works to be performed by a computer system. The CloudSim toolkit supports creation of one or supplementary virtual machines (VMs) on a simulated node of a Data Center, jobs, and their mapping to fitting VMs. It also allows simulation of multiple Data Centers to enable a study on federation and associated policies for migration of VMs for reliability and automatic scaling of applications. A first-class scheduler adapts its scheduling strategy according to the changing environment and the type of task. In paper we presented a Dynamic Fair Priority Task Scheduling Algorithm for efficient execution of task and comparison with FCFS and Round Robin Scheduling. Algorithm should be tested in cloud Sim toolkit and result shows that it give better performance compared to other conventional scheduling algorithm.