Abstract-Although there are few efficient algorithms in the literature for scientific workflow tasks allocation and scheduling for heterogeneous resources such as those proposed in grid computing context, they usually require a bounded number of computer resources that cannot be applied in Cloud computing environment. Indeed, unlike grid, elastic computing, such as Amazon's EC2, allows users to allocate and release compute resources on-demand and pay only for what they use. Therefore, it is reasonable to assume that the number of resources is infinite. This feature of Clouds has been called "illusion of infinite resources". However, despite the proven benefits of using Cloud to run scientific workflows, users lack guidance for choosing between multiple offering while taking into account several objectives which are often conflicting.On the other side, the workflow tasks allocation and scheduling have been shown to be NP-complete problems. Thus, it is convenient to use heuristic rather than deterministic algorithm. The objective of this paper is to design an allocation strategy for Cloud computing platform. More precisely, we propose three complementary bi-criteria approaches for scheduling workflows on distributed Cloud resources, taking into account the overall execution time and the cost incurred by using a set of resources.
International audienceThe Cloud computing paradigm is adopted for its several advantages like reduction of cost incurred when using a set of resources. Despite the many proven benefits of using a Cloud infrastructure to run business processes, it is still faced with a major problem that can compromise its success: the lack of guidance for choosing between multiple offerings. To ensure this, we propose a set of algorithms for business process scheduling in Cloud computing environments. More precisely, we propose an extension of our previous approaches taking into account the fact that several instances of the same process can run simultaneously, and they may have to share the same resources. The proposed approaches take into account the Cloud elasticity feature on the one hand, and on the other hand, they consider the two most important quality of service criteria when running business process in Clouds environment, namely (i) the overall execution time and (ii) the cost incurred using a set of resources. In addition they allow to ensure fairness between the different concurrent business process instances
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