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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%.