首页> 外文期刊>Soft Computing - A Fusion of Foundations, Methodologies and Applications >Genetic fuzzy rule-based scheduling system for grid computing in virtual organizations
【24h】

Genetic fuzzy rule-based scheduling system for grid computing in virtual organizations

机译:基于遗传模糊规则的虚拟组织网格计算调度系统

获取原文
获取原文并翻译 | 示例

摘要

One of the most challenging problems when facing the implementation of computational grids is the system resources effective management commonly referred as to grid scheduling. A rule-based scheduling system is presented here to schedule computationally intensive Bag-of-Tasks applications on grids for virtual organizations. There exist diverse techniques to develop rule-base scheduling systems. In this work, we suggest the joining of a gathering and sorting criteria for tasks and a fuzzy scheduling strategy. Moreover, in order to allow the system to learn and thus to improve its performance, two different off-line optimization procedures based on Michigan and Pittsburgh approaches are incorporated to apply Genetic Algorithms to the fuzzy scheduler rules. A complex objective function considering users differentiation is followed as a performance metric. It not only provides the conducted system evaluation process a comparison with other classical approaches in terms of accuracy and convergence behaviour characterization, but it also analyzes the variation of a wide set of evolution parameters in the learning process to achieve the best performance.
机译:面对计算网格的实现时最具挑战性的问题之一是通常称为网格调度的系统资源有效管理。这里介绍了一个基于规则的调度系统,用于在网格上为虚拟组织调度计算密集型任务包应用程序。存在多种开发基于规则的调度系统的技术。在这项工作中,我们建议加入任务的收集和排序标准以及模糊调度策略。此外,为了允许系统学习并因此改善其性能,基于密歇根州和匹兹堡方法的两种不同的离线优化程序被合并以将遗传算法应用于模糊调度器规则。遵循考虑用户差异的复杂目标函数作为性能指标。它不仅为进行的系统评估过程提供了与其他经典方法在准确性和收敛行为表征方面的比较,而且还分析了学习过程中各种进化参数集的变化以实现最佳性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号