摘要
在Hadoop分布式文件系统(HDFS)云存储环境下,网络带宽和节点性能有限且动态变化,现有的副本选择策略无法根据环境的变化选择最合适副本。针对这一问题,提出一种综合考虑了网络带宽、节点I/O性能以及节点存储空间等因素,基于灰色马尔可夫链预测模型的副本选择策略,以此在系统可用性和负载均衡性之间寻求一个平衡。最后通过仿真实验,验证了该策略的可行性与有效性。
In Hadoop Distributed File System（HDFS） where the network bandwidth and performance of nodes are limited and changed dynamically,the current strategy of replica selection can not adopt the most suitable replica according to the changes of the environment.Aiming at this problem,a new strategy of replica selection based on grey Markov chain prediction model which takes network band width,performance of I/O and storage space of nodes into the comprehensive consideration was proposed to seek a balance between system usability and load balancing.Simulation experimental results prove the validity and practicability of this new strategy.
出处
《计算机应用》
CSCD
北大核心
2011年第A02期39-42,共4页
journal of Computer Applications
基金
国家自然科学基金资助项目(70801036)
