Cloud Computing is gaining more and more attention among enterprises thanks to its high performance and low operating cost. Particularly, Cloud resources are used to deploy enterprises' business processes which are constrained by hard timing requirements. Similarly, Cloud providers propose resources in various pricing strategies based on temporal perspective. Taking into consideration both the time constraints and the variety of Cloud pricing strategies helps enterprises to achieve cost-effective process execution plans. Basically, to minimize process costs, stakeholders need to decide the execution time of process activities that overlaps with the temporal interval of the cheapest pricing strategy. In this paper, we present an approach to optimally schedule activities without violating their temporal constraints and capacity requirements. To do so, we use a mixed integer programming model with an objective function under a set of constraints. Our approach has been implemented and the experimental results highlight its performance and effectiveness