Live Migration of Multiple Virtual Machines with Resource Reservation in Cloud Computing Environments

Abstract

Virtualization technology is currently becoming increasingly popular and valuable in cloud computing environments due to the benefits of server consolidation, live migration, and resource isolation. Live migration of virtual machines can be used to implement energy saving and load balancing in cloud data center. However, to our knowledge, most of the previous work concentrated on the implementation of migration technology itself while didn't consider the impact of resource reservation strategy on migration efficiency. This paper focuses on the live migration strategy of multiple virtual machines with different resource reservation methods. We first describe the live migration framework of multiple virtual machines with resource reservation technology. Then we perform a series of experiments to investigate the impacts of different resource reservation methods on the performance of live migration in both source machine and target machine. Additionally, we analyze the efficiency of parallel migration strategy and workload-aware migration strategy. The metrics such as downtime, total migration time, and workload performance overheads are measured. Experiments reveal some new discovery of live migration of multiple virtual machines. Based on the observed results, we present corresponding optimization methods to improve the migration efficiency.