Workflow systems have become a major vehicle for easy and efficient development of scientific applications. This type of systems can benefit from the resource provisioning technology offered by the cloud computing. In fact, the latter offers on-demand virtualized resources to its users. These virtual resources can be added and released dynamically. Also, users are charged on a pay-per-use basis. How to make appropriate decisions when allocating resources to the tasks and dispatching the computing tasks to resource pool has become the main issue in cloud computing. The amount of allocated resources affects the execution time of the applications and the cost incurred by the user. In fact, resource under-provisioning will necessarily affect the performance. In contrast, over-provisioning can result in idle instances and cause additional costs. Then, efficient scheduling algorithms are required for selection of best suitable resources for task execution. This paper focuses on some of the important workflow scheduling strategies. It brings out an exhaustive survey of such strategies in cloud computing and includes a detailed classification of them. Then, it presents a comparative analysis of the studied approaches. Finally, it stands out a critical challenge for further research.

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