摘要
云计算环境中大数据应用在数据迁移方面遇到各种问题,主要表现为如何在迁移过程中减少网络访问次数,减少全局时间消耗,以及在提高效率的同时兼顾全局的负载均衡等。为此,对数据迁移进行建模,描述动态迁移策略,分别针对策略中的全局时间消耗、网络访问次数和全局负载均衡3个参数进行求解,并在云计算仿真平台Cloudsim下进行实验。结果表明,使用数据动态迁移策略后,任务完成时间比Zipf分布减少约10%,网络访问次数低于原始Zipf分布并趋于稳定;全局负载均衡方面,节点存储空间方差趋于0。
Big data applications meet various challenges in data migration in cloud computing environment. It mainly manifests in below aspects： reduce the number of network access, reduce the overall time consumption and improve the efficiency by the time of balancing the global load in the migration process and so on. Facing these challenges,it builds the problem model and descripts the dynamic migration strategy, then solves the global time consumption of data migration, the number of network access and global load balance in these three parameters. The cloud computing simulation experiment is done under Cloudsim experimental platform. The result shows that the proposed data dynamic migration strategy makes the task completion time reduced by 10% than Zipf distribution, network access number be lower than Zipf and tends to be stable. And in global load,the variance of the node＇ s store space is closed to zero.
出处
《计算机工程》
CAS
CSCD
北大核心
2016年第5期13-17,共5页
Computer Engineering
基金
国家自然科学基金资助项目(51467007)
云南省应用基础研究计划基金资助项目(2013FZ020)
关键词
云计算
大数据
负载均衡
数据迁移
网络访问
数据集
cloud computing
big data
load balance
data migration
network access
dataset
