共被期刊论文引用了3次
您的检索式：您选中1篇文献正在查看引证文献汇总
|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | 基于决策树模型的分布式存储数据纠删码修复显示文摘当今大数时代背景下,海量大数据的存储备份时刻冲击着当前先进的数据存储与纠删技术。分布式数据存储系统作为经典数据容错技术,在进行数据保障的过程中采用容错技术、多副本存储备份技术以及误码数据纠删等方式来保证数据存储的可靠性。纠删码技术以其数据存储过程中资源消耗低、可靠性高等优点在数据纠删存储领域得到了广泛应用,但是传统纠删技术依然存在数据修复速度低、修复率低等缺点。因此,结合数据决策模型提出基于决策树模型的分布式数据纠删码修复算法。算法首先建立决策树模型,然后将决策树与纠删码技术相结合建立纠删决策树模型。最后,给出了对应的数据仿真,同时实验对比可以看出提出的决策树纠删数据模型在修复速度、数据修复率、容错性等方面具有很好的有效性。 | 沈洪敏 周功建 | 2022 | 计算机仿真2022，39，6： | 2 |
| 2 | Scalable local reconstruction code design for hot data reads in cloud storage systems显示文摘Since demand for data is significantly heterogeneous in cloud storage systems(CSSs),there is traffic congestion in nodes storing hot data.In erasure-coded CSSs,traffic congestion can be alleviated by degraded reads sacrificing the bandwidth of surviving nodes.Local reconstruction codes(LRCs)reduce the bandwidth consumption of degraded reads,but cannot provide skewed throughput gain for the hot data.In this paper,we propose a scalable local reconstruction code(SLRC)that relies on LRCs but is more flexible in improving the throughput of a specific data block.First,we develop the local maximum throughput(LMT)to measure the maximum throughput of the hot data blocks by analyzing the actual read arrival rate of LRCs.Further,we elaborate on the structure of SLRC and analyze their performance metrics,which include storage overhead,reconstruction cost,and LMT.To select the appropriate code,we present the minimum reconstruction cost,minimum storage overhead,and minimum penalty algorithms.Finally,we implement extensive experiments on several typical SLRCs on the Hadoop distributed file system.Higher LMT and lower bandwidth consumption can be provided by SLRCs for hot data block degraded reads in CSSs compared with RS codes and LRCs. | Zhikai ZHANG Shushi GU Qinyu ZHANG | 2022 | Science China(Information Sciences)2022，65，12： | 1 |
您所在的机构暂未开通此部分的功能，请联系管理员