Abstract:Host-overloading detection is an important phase in the dynamic Virtual Machines (VMs) consolidation process. Using machine learning to predict the future workload on a host, is a very promising technique to avoid the overload host situation. In this work, we propose a novel approach for overloaded hosts detection, based on neural network and Markov model. The neural network is trained on a workload data set composed of VMs CPU-utilization history. The trained model is then used to predict the future usage for… Show more
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