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Decentralized Grid Scheduling with Evolutionary Fuzzy Systems

机译：演化模糊系统的分散网格调度

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摘要

In this paper, we address the problem of finding workload exchange policies for decentralized Computational Grids using an Evolutionary Fuzzy System. To this end, we establish a non-invasive collaboration model on the Grid layer which requires minimal information about the participating High Performance and High Throughput Computing (HPC/HTC) centers and which leaves the local resource managers completely untouched. In this environment of fully autonomous sites, independent users are assumed to submit their jobs to the Grid middleware layer of their local site, which in turn decides on the delegation and execution either on the local system or on remote sites in a situation-dependent, adaptive way. We find for different scenarios that the exchange policies show good performance characteristics not only with respect to traditional metrics such as average weighted response time and utilization, but also in terms of robustness and stability in changing environments.
机译：在本文中，我们解决了使用演化模糊系统为分散式计算网格查找工作负载交换策略的问题。为此，我们在网格层上建立了一个非侵入性的协作模型，该模型需要有关参与的高性能和高吞吐量计算（HPC / HTC）中心的最少信息，而使本地资源管理者完全不受影响。在这种完全自治的站点环境中，假定独立用户将其作业提交到其本地站点的Grid中间件层，而后者又取决于情况，决定是在本地系统还是在远程站点上进行委派和执行，自适应方式。我们发现在不同情况下，交换策略不仅在传统指标（例如平均加权响应时间和利用率）方面表现出良好的性能特征，而且在变化环境中的鲁棒性和稳定性方面也表现出良好的性能。

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