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机构地区:[1]国防科学技术大学计算机学院,长沙410073
出 处:《北京信息科技大学学报(自然科学版)》2014年第6期1-6,共6页Journal of Beijing Information Science and Technology University
基 金:国家自然科学基金资助项目(61120106005);国家863计划资助项目(2012AA01A309;2012AA01A301)
摘 要:当前,在分布式云文件系统中,纠删码冗余技术以较高的容错性能和较大的空间利用率逐步取代副本冗余技术来保证数据的可靠性。多数基于纠删码的云文件系统中,数据放置方法采用随机放置策略并假设集群节点同构,然而在实际的云存储系统中节点的同构性并不理想,且节点的存储性能会随着系统的运行动态地发生变化,所以随机地选取节点进行数据放置并不能有效地保证系统的均衡性。为此,文中分析确定了影响节点负载性能的关键因素,并采用层次分析法建模求出不同存储数据类型的负载影响因子。同时基于节点负载性能,计算提出了一种全局随机、局部顺序的数据放置算法,该算法在选择节点的过程中综合考虑节点内的实时负载均衡和数据可靠性两个因素。实验结果显示,相比于随机放置方法,提出的该数据放置方法不仅能够实现存储系统节点内的实时负载均衡,还能加快数据写入和恢复的速度。In the distributed cloud file system, erasure code redundant technology has gradually replaced the replication redundant technology with its high fault-tolerance performance and large space utilization to ensure the reliability of the data. In most cloud file system based on erasure code, random placement strategy is used as data placement method and the cluster nodes are assumed to be homogeneous. However, in the real cloud file system, isostructuralism of cluster nodes is not ideal and storage performance of cluster nodes changes dynamically with the system running. Thus, the random selection of nodes for data placement cannot effectively guarantee the balance of system. Therefore, the key factors which influence the node load performance are analyzed, and Analytic Hierarchy Process is used to model to get these key factors. Based On node load performance, a data placement algorithm is calculated and proposed by placing global data randomly and local data in order. This algorithm comprehensively considers the real-time load performance of the nodes and the node distribution balance in the process of selecting the nodes. Experimental results show that, compared to the random placement method, the method of data placement can not only realize real-time load balance of storage system, but also can improve the speed of writing and recovering data.
分 类 号:TP311[自动化与计算机技术—计算机软件与理论]
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