VHaul: Towards Optimal Scheduling of Live Multi-VM Migration for Multi-tier Applications

Abstract

Live virtual machine (VM) migration enables seamless movement of an online server from one location to another to achieve failure recovery, load balancing, and system maintenance. Beyond single VM migration, a multi-tier application involves a group of correlated VMs and its live migration will require careful scheduling of the migrations of the member VMs. Our observations from extensive experiments using a variety of multi-tier applications suggest that, in a dedicated data center with dedicated migration links, different migration strategies result in distinct performance impacts on a multi-tier application. The root cause of the problem is the inter-dependence between functional components of a multitier application. We leverage these observations in vHaul, a system that coordinates multi-VM migration to approximate the optimal scheduling. Our evaluation of a vHaul prototype on Xen suggests that vHaul yields the optimal multi-VM live migration schedules. Further, our application-level evaluation using Apache Olio, a web 2.0 cloud application, shows that the optimal migration schedule produced by vHaul outperforms the worst-case schedule by 43% in application throughput. Moreover, the optimal schedule significantly reduces service latency during migration by up to 70%.