Cloud has emerged into another enhancement that manipulates the diversity of resources in order to expand the ability of Cloud facility. Cloud is no longer being seen as one-type service provider. The advantages of the heterogeneous Cloud give great benefits to the users and have business potential in service market. To cope with the dynamic nature of heterogeneous Cloud, the Cloud provider needs to have strategies to efficiently allocate tasks to the resources. Also, to charge the services is another challenge to the Cloud provider as the resources in the Cloud system are heterogeneous. In this study, we suggest the implementation of a. Multi-level priority-based scheduling and dynamic pricing into the heterogeneous Cloud model. We perform an extensive performance evaluation on the model through simulations. We define the attribute of the Cloud simulation as dynamic and random to address the heterogeneous feature of the Cloud. Our simulation result shows that the multi-level priority-based is significantly increasing the resource utilization rate and its integration with the dynamic pricing successfully improves the performance of the Cloud service in term of satisfaction rate.

Large computing systems where globally distributed can be best characterized by their dynamic nature particularly in terms of resource provisioning and scheduling. Users of the systems normally aim to maximize their own interest when consuming the shared resources. Apart from that, the processing requirements that submitted by the systems' users are diverse in their properties (e.g., size, priority). This condition makes the resources in distributed system overwhelmed by heterogeneity of task to be processed; that leads to fluctuation in resource availability. There are researchers' proposed scheduling algorithms and evaluated through simulation system in order to improve resource availability. It is because the simulation system is able to save cost rather than real test bed experimental. In response to this, we proposed priority-based scheduling algorithm for improving resource availability that developed using discrete-event simulation approach. We defined several events in the simulation to represent various execution statuses that used to monitor resource state in the distributed systems. Our simulation system successfully gives better performance in terms of waiting time compared than other works that also used simulation as their experimental platform.