Abstract
Conference Title: 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA) Conference Start Date: 2018, Nov. 1 Conference End Date: 2018, Nov. 3 Conference Location: Cambridge, MA, USA 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. 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 presents a new proposal for the dynamic adjustment of threshold values that aims to minimize the number of migrations in varying workload environments. The proposed approach, named the ‘dynamic threshold-based fuzzy approach’ (DTFA), is a fuzzy threshold-based approach used for adjusting the threshold values of PMs in a cloud environment. The proposed approach allows the number of migrations caused by overloading to be reduced and SLAs to be met. Three sets of experiments with different workloads were conducted to validate the proposed approach. The results demonstrate that DTFA outperforms existing solutions by an average of 22.52%, 45.63% and 56.68% in power consumption, VM migration count, and SLA violations, respectively.