New comprehensive model based on virtual clusters and absorbing Markov chains for energy-efficient virtual machine management in cloud computing

Utilizing from energy-aware solutions along with maintaining service-level agreements is one of the most important research issues in cloud computing. In the proposed model, monitoring the status of resources and analysing the obtained data have led to proper placement and consolidation of virtual machines through targeted migrations at the right time. In the virtual machine placement policy, the definition of absorption mode has been used in simulated annealing algorithm in addition to the formation of virtual clusters to prevent from unlimited increase in the length of created Markov chain in any temperature while maintaining the convergence. The results of simulations obtained from various scenarios in CloudSim indicated the proposed model has led to energy savings up to 14.3%, 19% and 21% on low load, average load and high load, respectively, compared to the best understudy algorithm, while the SLA violation has also led to a decrease in all three modes.