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Cloud computing has emerged as a promising platform to execute scientific workflows. The size of such workflows could reach up to thousands of tasks, which have data dependency constraints. Accordingly, optimising the utilisation of the used resources is an essential factor in reducing the execution time and cost. This paper presents a Utility-based Algorithm (UBA) that works by assigning tasks to VMs based on a utility function that aims to minimise the execution cost and time. The results showed that the UBA had a significant impact on reducing the execution cost and makespan.