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Optimization of overlay distributed computing systems for multiple classifier system—heuristic approach

机译:用于多分类器系统的覆盖分布式计算系统的优化—启发式方法

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摘要

Recently, the volume of data produced in academia and industry has grown drastically. Distributed computing systems including Grids make use of computer networks (e.g. Internet) to share various computing resources around the world in order to improve the processing. Due to large data volumes being transferred between geographically spread computing nodes, network aspects of the computing systems have become significant. In this article, we introduce a model of an overlay distributed computing system, which could be used by for multiple classifier systems. We formulate an Integer Programming optimization problem with the objective to minimize the OPEX cost including processing and data transfer. Next, an effective heuristic algorithm based on the Greedy Randomized Adaptive Search Procedure (GRASP) approach is developed and examined.
机译:最近,学术界和工业界产生的数据量急剧增加。包括Grids在内的分布式计算系统利用计算机网络(例如Internet)在世界范围内共享各种计算资源,以改善处理能力。由于在地理上分散的计算节点之间传送了大数据量,所以计算系统的网络方面已经变得很重要。在本文中,我们介绍了覆盖分布式计算系统的模型,该模型可用于多个分类器系统。我们制定一个整数编程优化问题,目的是最大程度地减少包括处理和数据传输在内的OPEX成本。接下来,开发并研究了基于贪婪随机自适应搜索过程(GRASP)方法的有效启发式算法。

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  • 来源
    《Logic Journal of IGPL》 |2012年第4期|p.677-688|共12页
  • 作者单位

    Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland.E-mail: t.kacprzak{at}gmail.com;

    krzysztof.walkowiak{at}pwr.wroc.pl;

    michal.wozniak{at}pwr.wroc.pl;

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  • 正文语种 eng
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