A novel VM workload prediction using Grey Forecasting model in cloud data center

摘要: In recent years, the resource demands in cloud environment have been increased incrementally. order to effectively allocate resources, workload prediction of virtual machines (VMs) is a vital issue that makes VM allocation more instantaneous and reduces power consumption. this paper, we propose method using Grey Forecasting model VMs, which first string research field. Firstly, utilize time-dependent at same period every day, forecast tendency towards increasing or decreasing. Next, compare predicted value with previous time on usage, then determine migrate wherein physical machine (PM) for balanced lower The simulation results show our proposed not only uses fewer data predict accurately but also allocates VMs saving.