Workload-Aware VM Consolidation in Cloud Based on Max-Min Ant System

With the increasing consumption of energy in cloud data center, the cloud providers pay more attention to the green cloud computing for saving energy. The most effective way in green cloud computing is using virtual machine (VM) consolidation to pack VMs into a smaller amount of physical machines (PMs), which can save energy by switching off the idle PMs. However, in traditional static workload approach, VMs are over-provisioned with a static capacity to guarantee peak performance, which increases the unnecessary energy consumption. In this paper, we propose an innovative approach WAVMC to achieve efficient VM consolidation by using multi-dimensional time-varying workloads based on the Max-Min Ant System (MMAS). In the MMAS, we employ the complementary of both workload patterns and multi-dimensional resources usage as heuristic factors. Extensive simulations on production workloads demonstrate that the proposed model outperforms state-of-the-art baselines in active server counts and resources wastage.