一种新型的数据网格动态副本策略

许多科学实验和工程应用会产生TB或PB级的数据.这样庞大的数据体需要分布在世界不同地点的众多计算资源协同处理,高性能网格为使这些数据高效传送到地理上不同的位置提供了理想的手段.当用户频繁的访问大量远程数据时,动态副本可以有效地减少网格中的带宽消耗和访问延迟.在多层数据网格架构基础上提出了一种新型的动态副本策略:快速瀑布模型算法.Op-torSi m仿真器也被修改用以适应这种新型的策略.仿真结果表明,在随机访问模式下,对比FastSpread,LRU和Economy-Zipf ,快速瀑布策略能有效地减少平均数据访问时间,并且其优势随着用户提交作业数量的增加而增大.

A New Dynamic Replication Strategy for Data Grid

Scientific experiments and engineering applications generate large amounts of data which need to be shared among researchers around the world. High performance grids facilitate the distribution of such data to geographically remote places. Dynamic replication is a practical and efficient method which can be used to reduce bandwidth consumption and access latency in high performance data grids where users require remote access to large files. In this paper, a new dynamic replication algorithm, Fast Cascading, is proposed for the multi-tier Data Grid. Simulator OptorSim has been modified to illustrate the performance of the replication algorithm. The simulation results show that this algorithm can reduce the average response time of data access greatly for random access pattern compared to Fast Spread, LRU and Economy-Zipf dynamic replication strategy and the gain increases with the number of submitted jobs.