中文摘要：

Key／Value存储系统在大规模、高性能云应用支撑方面扮演了重要的角色，对云端Key／Value存储系统而言，数据迁移是实现节点动态扩展与弹性负载均衡的关键技术．如何降低迁移开销，是云服务提供商需着力解决的问题．已有研究工作大多针对非虚拟化环境下的数据迁移问题，这些方法对于云端Key／Value存储系统而言往往并不适用．为应对上述挑战，将数据迁移问题纳入负载均衡场景解决．提出一种基于面积的迁移开销模型，该模型可以有效感知底层VM性能干扰状况，权衡迁移时间与性能衰减值．进一步提出一种开销敏感的数据迁移算法，该算法基于开销模型与均衡度制订数据迁移计划，选取最优的迁移操作．基于雅虎的云服务基准测试工具YCSB验证了该方法的有效性．

英文摘要：

Key-Value stores play an important role in today＇s large-scale, high-performance cloud applications. Elastic scaling and load rebalancing with low cost live data migration are critical to enabling the elasticity of Key/Value stores in the cloud. Learning how to reduce the migration cost is one difficult problem that cloud providers are trying to solve. Many existing works try to address this issue in non-virtual environments. These approaches, however, may not be well suited for cloud-based Key/Value stores. To address this challenge, the study tackles the data migration problem under a load rebalancing scenario. The paper builds a one cost model that could be aware of the underlying VM interference and trade-off between migration time and performance impact. A cost-aware migration algorithm is designed to utilize the cost model and balance rate to guide the choice of possible migration actions. Our evaluation using Yahool Cloud Serving Benchmark shows the effectiveness of the approach.