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Energy efficiency is becoming a very important concern for Cloud Computing environments. These are normally composed of large and power consuming data centers to provide the required elasticity and scalability to their customers. In this context, many efforts have been developed to balance the loads at host level. However, determining how to maximize the resources utilization at Virtual Machine (VM) level still remains as a big challenge. This is mainly driven by very dynamic workload behaviors and a wide variety of customers' resource utilization patterns. This paper introduces a dynamic resource provisioning mechanism to over-allocate the capacity of real-time Cloud data centers based on customer utilization patterns.
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