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Live migration of virtual machines is a key management function in cloud computing. Unfortunately, no live migration progress management system exists in the state-ofthe- art, leading to (1) guesswork over how long a migration might take and the inability to schedule dependent tasks accordingly; (2) unacceptable application degradation when application components become split over distant cloud datacenters for an arbitrary period during migration; (3) inability to tradeoff application performance and migration time e.g. to finish migration later for less impact on application performance. Pacer is the first migration progress management system that solves these problems. Pacer's techniques are based on robust and lightweight run-time measurements of system and workload characteristics, efficient and accurate analytic models for progress predictions, and online adaptation to maintain user-defined migration objectives for coordinated and timely migrations. Our experiments on a local testbed and on Amazon EC2 show that Pacer is highly effective under a range of application workloads and network conditions.
Zheng et al. (Sun,) studied this question.
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