Abstract
Dynamic virtual machine (VM) consolidation is considered an effective approach for improving power consumption and computing resource utilization in cloud-based data centers. However, the ever-changing workload in a data center makes it difficult for VM consolidation to prevent service level agreement (SLA) violations and optimize power consumption. The detection of overutilized and underutilized physical machines (PMs) plays a significant role in effective VM consolidation, immediately improving resource utilization, SLA violations, and power consumption. This paper proposes the dynamic threshold-based fuzzy approach (DTFA) for detecting overloaded and underutilized PMs, and the Lowest Interdependence Factor Exponent Multiple Resources Predictive (LIFE-MP) approach for VM placement, by considering multiple computing resources being used simultaneously in a cloud environment. The DTFA is a fuzzy threshold-based approach used to adjust the threshold values of PMs in a cloud environment. The LIFE-MP approach selects a PM at which to place the migrating VM, based on the PM with the lowest correlation coefficient value among the already-running VMs and the migrating VM to reduce performance degradation because of the VM migration. The comparison between LIFE-MP scheme and a power-aware best-fit decreasing (PABFD) scheme shows that the proposed scheme reduces power consumption by 22.52%, SLA violations by 45.63%, and the number of VM migrations by 56.68%.