以顾及信息熵构造判定树为核心,在此基础上提出了顾及信息熵构造判定树(Information entropy construction decision tree,IECDT)的网络数据库搜索算法。借助于信息熵构造判定树构建了对应的抽象模型,之后在该数据基础上分析得到了网络...以顾及信息熵构造判定树为核心,在此基础上提出了顾及信息熵构造判定树(Information entropy construction decision tree,IECDT)的网络数据库搜索算法。借助于信息熵构造判定树构建了对应的抽象模型,之后在该数据基础上分析得到了网络数据库搜索算法。实验表明:与典型DS-means相比,文中所提的网络数据库搜索算法不仅能大幅度地减少网络数据间的通讯代价,还能提升平均10%左右的网络数据库搜索效率。展开更多
To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured Parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the sch...To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured Parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the scheme, two algorithms are proposed for the construction of multiple regeneration trees, namely the edge-disjoint algorithm and edge-sharing algorithm. The edge-disjoint algorithm constructs multiple independent trees, and is simple and appropriate for environments where newcomers and their providers are distributed over a large area and have few intersections. The edge-sharing algorithm constructs multiple trees that compete to utilize the bandwidth, and make a better utilization of the bandwidth, although it needs to measure the available band-width and deal with the bandwidth changes; it is therefore difficult to implement in practical systems. The parallel regeneration for multiple data losses of TPR primarily includes two optimizations: firstly, transferring the data through the bandwidth optimized-paths in a pipe-line manner; secondly, executing data regeneration over multiple trees in parallel. To evaluate the proposal, we implement an event-based simulator and make a detailed comparison with some popular regeneration methods. The quantitative comparison results show that the use of TPR employing either the edge-disjoint algorithm or edge-sharing algorithm reduces the regeneration time significantly.展开更多
文摘以顾及信息熵构造判定树为核心,在此基础上提出了顾及信息熵构造判定树(Information entropy construction decision tree,IECDT)的网络数据库搜索算法。借助于信息熵构造判定树构建了对应的抽象模型,之后在该数据基础上分析得到了网络数据库搜索算法。实验表明:与典型DS-means相比,文中所提的网络数据库搜索算法不仅能大幅度地减少网络数据间的通讯代价,还能提升平均10%左右的网络数据库搜索效率。
基金supported by the National Grand Fundamental Research of China (973 Program) under Grant No. 2011CB302601the National High Technology Research and Development of China (863 Program) under GrantNo. 2013AA01A213+2 种基金the National Natural Science Foundation of China under Grant No. 60873215the Natural Science Foundation for Distinguished Young Scholars of Hunan Province under Grant No. S2010J5050Specialized Research Fund for the Doctoral Program of Higher Education under Grant No. 20124307110015
文摘To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured Parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the scheme, two algorithms are proposed for the construction of multiple regeneration trees, namely the edge-disjoint algorithm and edge-sharing algorithm. The edge-disjoint algorithm constructs multiple independent trees, and is simple and appropriate for environments where newcomers and their providers are distributed over a large area and have few intersections. The edge-sharing algorithm constructs multiple trees that compete to utilize the bandwidth, and make a better utilization of the bandwidth, although it needs to measure the available band-width and deal with the bandwidth changes; it is therefore difficult to implement in practical systems. The parallel regeneration for multiple data losses of TPR primarily includes two optimizations: firstly, transferring the data through the bandwidth optimized-paths in a pipe-line manner; secondly, executing data regeneration over multiple trees in parallel. To evaluate the proposal, we implement an event-based simulator and make a detailed comparison with some popular regeneration methods. The quantitative comparison results show that the use of TPR employing either the edge-disjoint algorithm or edge-sharing algorithm reduces the regeneration time significantly.
