超立方体系统中基于图的子多维数据集分配和任务迁移

O. Kang, B.M. Kim, H. Yoon, S. Maeng, J. Cho
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引用次数: 3

摘要

针对超立方体中的碎片问题,提出了一种基于启发式子立方体分配(HSA)策略的任务迁移方案。该方案称为CSC(互补子立方体合并),使用启发式和无向图,称为SC(子立方体)图。如果由于系统碎片而无法满足传入请求,则执行任务迁移方案以生成更高维度的子数据集。仿真结果表明,在自适应模式下,HSA策略比Buddy和GC策略具有更高的效率。此外,HSA策略的迁移成本明显低于Buddy和GC策略
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A graph-based subcube allocation and task migration in hypercube systems
The authors propose a task migration scheme based on the HSA (heuristic subcube allocation) strategy to solve the fragmentation problem in a hypercube. This scheme, called CSC (complementary subcube coalescence), uses a heuristic and an undirected graph, called the SC (subcube) graph. If an incoming request is not satisfied due to the system fragmentation, the task migration scheme is performed to generate higher dimension subcubes. Simulation results show that the HSA strategy gives better efficiency than the Buddy and GC strategies in the adaptive mode. Moreover, the HSA strategy has a significantly lower migration cost than that of the Buddy and GC strategies.<>
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