Data stored on a cloud is becoming more and more important. Thus, data replication across multiple cloud nodes is considered an effective solution to achieve good performance in terms of response time, load balancing and most importantly, high data availability and reliability. To maximize the benefit of data replication, strategic placement of replicas in the system is critical. In this paper, the vision of replicas management is turned to multi-criteria optimization methods, again known as Multiple-Criteria Decision Analysis (MCDA) for decision support system. For this, we propose a data replication strategy in a cloud environment based on two different methods. The first is based on the Analytic Hierarchy Process (AHP), and the second is based on the ELECTRE-I multi-criteria decision support method. The main aim is to propose and demonstrate the use of an AHP and ELECTRE-I models for cloud data replication. The results of simulations of our strategy were satisfactory and improved performances, with the two methods, by comparing it with other strategy proposed in the literature.
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