Virtual machine migration in an over-committed cloud

While early emphasis of Infrastructure as a Service (IaaS) clouds was on providing resource elasticity to end users, providers are increasingly interested in over-committing their resources to maximize the utilization and returns of their capital investments. In principle, over-committing resources hedges that users — on average — only need a small portion of their leased resources. When such hedge fails (i.e., resource demand far exceeds available physical capacity), providers must mitigate this provider-induced overload, typically by migrating virtual machines (VMs) to underutilized physical machines. Recent works on VM placement and migration assume the availability of target physical machines [1], [2]. However, in an over-committed cloud data center, this is not the case. VM migration can even trigger cascading overloads if performed haphazardly. In this paper, we design a new VM migration algorithm (called Scattered) that minimizes VM migrations in over-committed data centers. Compared to a traditional implementation, our algorithm can balance host utilization across all time epochs. Using real-world data traces from an enterprise cloud, we show that our migration algorithm reduces the risk of overload, minimizes the number of needed migrations, and has minimal impact on communication cost between VMs.