全局负载均衡下云环境中的大数据动态迁移方法  

Big Data Dynamic Migration Method Based on Global Load Balancing in Cloud Environment

作　　者：章勇 张洁卉 柳斌 

机构地区：[1]华中科技大学网络与计算中心,武汉430074

出　　处：《计算机科学》2018年第1期196-199,共4页Computer Science

基　　金：华中科技大学自主创新基金项目(2015MS139);国家自然科学基金:3D H.264视频的无帧内失真漂移隐写方法研究(61272407)资助

摘　　要：在云环境中,数据负载均衡化速度较慢且易出现数据倾斜,这严重干扰了系统状态。为了减小数据迁移的代价,提出一种在全局负载均衡下云环境中的大数据动态迁移方法。首先构造负载均衡模型,在均衡负载下计算数据迁移成本,并给出最小数据迁移成本模型。计算数据迁移成本并评估虚拟机数据负载资源利用率,从而使数据重载的服务器转移到数据轻载的服务器上,达到云环境中的数据均衡化。仿真实验结果证明,所提方法提高了数据负载的均衡化速度和均衡效率,降低了数据迁移成本,且提高了资源利用率。In the cloud environment,the data load equalization is slow and the data skew.In order to reduce the cost of data transfer,aglobal load balancing method of dynamic data migration under the cloud environment was proposed.First,load balancing model was constructed,data migration cost was computed in load balancing,and the minimum cost of data migration model was given.The cost of data transfer was calculated,and the utilization ratio of virtual machine data load was evaluated so that the data overloaded server can be transferred to the data server.The simulation results show that the proposed method improves the speed and efficiency of data load balancing,reduces the cost of data migration,and improves the utilization ratio of resources.

关 键 词：负载均衡 资源利用率 数据迁移 

分 类 号：TN393[电子电信—物理电子学]