Shrinker: Improving Live Migration of Virtual Clusters over WANs with Distributed Data Deduplication and Content-Based Addressing

Live virtual machine migration is a powerful feature of virtualization technologies. It enables efficient load balancing, reduces energy consumption through dynamic consolidation, and makes infrastructure maintenance transparent to users. While live migration is available across wide area networks with state of the art systems, it remains expensive to use because of the large amounts of data to transfer, especially when migrating virtual clusters rather than single virtual machine instances. As evidenced by previous research, virtual machines running identical or similar operating systems have significant portions of their memory and storage containing identical data. We propose Shrinker, a live virtual machine migration system leveraging this common data to improve live virtual cluster migration between data centers interconnected by wide area networks. Shrinker detects memory pages and disk blocks duplicated in a virtual cluster to avoid sending multiple times the same content over WAN links. Virtual machine data is retrieved in the destination site with distributed content-based addressing. We implemented a prototype of Shrinker in the KVM hypervisor and present a performance evaluation in a distributed environment. Experiments show that it reduces both total data transferred and total migration time.