Virtual Machine Migration Techniques for Optimizing Energy Consumption in Cloud Data Centers

The energy used by cloud data centers (CDCs) to support large volumes of storage and computation is dramatically increasing as the scope services continues expand. This puts a greater burden on environment results in higher expenses for providers. Virtualization migration consolidation have been widely current CDCs achieve ser-vice reduce consumption (EC). study divides fundamental tasks virtual machine (VM) into three portions: determining timing, choosing VMs migrate out, selecting destination hosts. An EC levels-based adaptive dynamic threshold method timing was proposed, well correlation utilization-based strategy out an improved EC-aware best-fit algorithm pro-posed algorithms were evaluated using CloudSim toolbox, real VM workload traces from PlanetLab experimental data. According experiments, proposed EC, service level agreement violation (SLAV), number migrations average 15.49%, 7.85%, 83.32% comparison related state-of-the-art methods benchmark algorithms. suggests that outperform other techniques migration, even when necessitates significant or amount host resources, improve quality while optimizing consumption. However, experiments conducted simulation platform, which has some drawbacks, leading varying slightly actual environment.