Abstract

Virtualization technology, as the technical support for cloud computing, frees users from the limitations of hardware resources. Dynamic migration technology enables virtual machines to be moved across hosts, and services running on the virtual machines are basically uninterrupted during the migration process, which greatly facilitates the maintenance work in the data center. However, dynamic migration needs to transmit a large amount of repeated data. In order to improve the migration efficiency, this paper conducts the following research on the original pre-copy algorithm. First, we introduce a high dirty page determination algorithm based on the locality principle to classify memory pages and propose an improved memory migration pre-copy algorithm on this basis. Second, in order to solve the problem that the pre-copy algorithm cannot converge under a high load, an improved VM downtime determination algorithm is proposed. Third, the paper also introduces the LZ4 compression algorithm to further optimize the memory migration process. Finally, this paper implements the above optimization scheme on a KVM platform and tests its performance. It is compared with the native pre-copy algorithm and Three-Phase Optimization algorithm (TPO). The result shows that the optimized scheme significantly reduces the total migration time and downtime.

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