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Virtual machine migration enables load balancing, hot spot mitigation and server consolidation in virtualized environments. Live VM migration can be of two types - adaptive, in which the rate of page transfer adapts to virtual machine behaviour (mainly page dirty rate), and non-adaptive, in which the VM pages are transferred at a maximum possible network rate. In either method, migration requires a significant amount of CPU and network resources, which can seriously impact the performance of both the VM being migrated as well as other VMs. This calls for building a good understanding of the performance of migration itself and the resource needs of migration. Such an understanding can help select the appropriate VMs for migration while at the same time allocating the appropriate amount of resources for migration. While several empirical studies exist, a comprehensive evaluation of migration techniques with resource availability constraints is missing. As a result, it is not clear as to which migration technique to employ under a given set of conditions. In this work, we conduct a comprehensive empirical study to understand the sensitivity of migration performance to resource availability and other system parameters (like page dirty rate and VM size). The empirical study (with the Xen Hypervisor) reveals several shortcomings of the migration process. We propose several fixes and develop the Improved Live Migration technique (ILM) to overcome these shortcomings. Over a set of workloads used to evaluate ILM, the network traffic for migration was reduced by 14-93% and the migration time was reduced by 34-87% compared to the vanilla live migration technique. We also quantified the impact of migration on the performance of applications running on the migrating VM and other co-located VMs.
Nathan et al. (Sun,) studied this question.