A Multi-resource Selection Scheme for Virtual Machine Consolidation in Cloud Data Centers

Abstract

Resources used in a cloud data center could be spread across a large number of servers that are not fully utilized. This situation results in significant operational costs which are directly related to the power consumption of active servers. Virtual machine migration enables reducing the number of active servers by consolidating the load on a limited amount of nodes. Several schemes have actually been proposed to consolidate virtual machines on the minimum number of physical servers in order to reduce power consumption. However, most of the existing solutions only consider a limited trade off among multiple types of resources, thus resulting in unnecessarily activated physical servers. This article proposes a multi-resource selection (MRS) scheme for consolidating virtual machines in cloud data centers. With MRS, each physical server is first characterized in terms of multiple types of resources and then classified through its overall resource utilization. Based on the MRS scheme, a balanced multiple-resource utilization algorithm is also used to spread the load across different types of resources while consolidating virtual machines. The proposed solution is evaluated through simulations on both synthetic and real-world workloads. Experimental results show that the proposed approach outperforms several existing schemes in terms of the number of active physical servers and the utilization of multiple resources.