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GRASP Algorithm for Optimization of Grids for Multiple Classifier System

机译:用于多分类器系统网格优化的GRASP算法

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摘要

In recent years the volume of data used in scientific researches and industry has increased significantly. Distributed computing systems including Grids use the public Internet to share computational resources of research institutions around the world in order to process the data. Due to large data volumes being transferred, network aspects of Grids have become important. In this work we introduce a model of an overlay Grid system, which could be used by the distributed recognition system based on the idea of combining classifiers. We formulate an Integer Programming optimization problem with the objective to minimize the overall cost including processing and data transfer. Next, an effective heuristic algorithm is developed to solve the problem. Results of numerical experiments showing the comparison of the heuristic against solutions provided by CPLEX solver are presented.
机译:近年来,科学研究和工业中使用的数据量大大增加。包括Grids在内的分布式计算系统使用公共Internet共享世界各地研究机构的计算资源,以便处理数据。由于要传输大量数据,因此网格的网络方面变得很重要。在这项工作中,我们介绍了覆盖网格系统的模型,该模型可以基于组合分类器的思想而被分布式识别系统使用。我们制定一个整数编程优化问题,目的是最大程度地降低包括处理和数据传输在内的总体成本。接下来,开发了一种有效的启发式算法来解决该问题。给出了数值实验的结果,该结果显示了启发式方法与CPLEX求解器提供的解决方案的比较。

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