A reliable energy-aware approach for dynamic virtual machine consolidation in cloud data centers

To achieve energy efficiency in data centers, dynamic virtual machine (VM) consolidation as a key technique has become increasingly important nowadays due to the significant amounts of power needed to operate these data centers. Most of the existing works on VM consolidation have been focused only on reducing the number of active physical machines (PMs) using VM live migration to prevent inefficient usage of resources. But on the other hand, high frequency of VM consolidation has a negative effect on the system reliability. Indeed, there is a crucial trade-off between reliability and energy efficiency, and to optimize the relationship between these two metrics, further research is needed. Therefore, in this paper a novel approach is proposed that considers the reliability of each PM along with reducing the number of active PMs simultaneously. To determine the reliability of PMs, a Markov chain model is designed, and then, PMs have prioritized based on their CPU utilization level and the reliability status. In each phase of the consolidation process, a new algorithm is proposed. A target PM selection criterion is also presented that by considering both energy consumption and reliability selects the appropriate PM. We have validated the effectiveness of our proposed approach by conducting a performance evaluation study using CloudSim toolkit. The simulation results show that the proposed approach can significantly improve energy efficiency, avoid inefficient VM migrations and reduce SLA violations.