Improving Virtual Machine live migration via application-level workload analysis

Abstract

Virtual Machine (VM) live migration is key for implementing resource management policies to optimize metrics such as server utilization, energy consumption, and quality-of-service. A fundamental challenge for VM live migration is its impact on both user and resource provider sides, including service downtime and high network utilization. Several VM live migration studies have been published in the literature. However, they mostly consider only system level metrics such as CPU, memory, and network usage to trigger VM migrations. This paper introduces ALMA, an Application-aware Live Migration Architecture that explores application level information, in addition to the traditional system level metrics, to determine the best time to perform a migration. Based on experiments with three real applications, by considering application characteristics to trigger the VM live migration, we observed a substantial reduction in data transferred over the network of up to 42% and the total live migration time decrease of up to 63%.