中文摘要：

为了改善数据重均衡的效果及减小数据迁移对系统性能的影响，提出一种上下文感知的数据重均衡方法。构建迁移时间预测模型，以刻画虚拟机环境上下文对数据迁移的影响，据此提出基于细粒度资源监测的上下文感知的数据重均衡算法CADR。实验结果表明，该迁移时间预测模型具有较低的错误率；CADR算法与传统数据重均衡算法相比，能够提供更好的均衡效果及更短的迁移时间。

英文摘要：

In order to improve the effect of data rebalancing and reduce the impact of data migration, a context-aware data reba- lancing approach is proposed. First, a predictive model of migration time is presented to depict the impact of virtualization con- text on data migration. Then a context-aware data rebalancing algorithm （CADR） is provided based on fine-grained resource mo- nitoring. The experiments show that our prediction model of migration time has a low error rate, and CADR can improve perfor- mance compared with a typical data rebalancing algorithm.