面向网格数据分析应用的协同数据分发方案

Tong Guo, S. Jarvis
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引用次数: 0

摘要

为支持网格的数据分析应用程序提出了一个三层数据分布框架。该框架基于现有的资源预留服务:该框架服务的分析任务及其输入数据由现有的性能感知调度系统分配给称为“计算器”的计算主机。一个所谓的“向导”组织从源服务器到“协调器”的数据传递,每个协调器安排从自己到所有计算器的数据传播。这种方案,我们称之为DIAO,是点对点(P2P),在下载数据项后,主机可以充当它的服务器。理论建模表明,数据分布的持续时间取决于覆盖层中瓶颈资源的有效利用,我们开发了三种启发式方法来最小化这一持续时间,并受可用资源的限制。通过仿真验证了DIAO开发有限资源的能力。
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DIAO: A Scheme of Cooperative Data Distribution for Grid-Enabled Data Analysis Applications
A three-tier data distribution framework is proposed for grid-enabled data analysis applications. This framework is based on existing resource reservation services: the analytical tasks which this framework serves, and their input data, are assigned by an existing performance-aware scheduling system to computational hosts termed 'calculators'. A so-called 'guider' organizes the data delivery from the source server to the 'coordinators', and every coordinator schedules the data propagation from itself to all its calculators. This scheme, which we call DIAO, is peer-to-peer (P2P), in that after downloading a data item, a host may behave as its server. Theoretical modeling reveals that the duration of data distribution depends on the effective utilization of the bottleneck resource in the overlay, and we develop three heuristics to minimize this duration, subject to the available resources. The ability of DIAO to exploit limited resources is demonstrated through simulation.
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