...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Natural Computing >Cloud-based evolutionary algorithms: An algorithmic study
【24h】

Cloud-based evolutionary algorithms: An algorithmic study

机译：基于云的进化算法：算法研究

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper presents a cloud-computing based evolutionary algorithm using a synchronous storage service as pool for exchange information among population of solutions. The multi-computer was composed of several normal PCs or laptops connected via Wifi or Ethernet. In this work the effect of how the distributed evolutionary algorithm reached the solution when new PCs was added was tested whether that effect also translates to the algorithmic performance of the algorithm. To this end different (and hard) problems was addressed using the proposed multi-computer, analyzing the effects that the automatic load-balancing and synchronization had on the speed of algorithm successful, and analyzing how the number of evaluation per second increases when the multi-computer includes new nodes. The measure used for the analysis was number of evaluation per second which was increased when the multi-computer includes new nodes. The algorithm solved the proposed problems and it was viable to run it in homogeneous or heterogeneous platforms. The experiments includes two problems and different configuration for the distributed evolutionary algorithm in order to check the results of the algorithm for several rates of information exchange with the selected storage service. Results shows that the system is viable with homogeneous or heterogeneous nodes and there is no significative differences for the synchronous storage services we have tested. But when the problem is harder, and the threads of the algorithm does not stop for each information exchange (migration of individual from one population to another one), the differences of using a specific service became significative in terms of success of the algorithm.
机译：本文提出了一种基于云计算的进化算法，该算法使用同步存储服务作为池来在解决方案群体之间交换信息。多计算机由几台通过Wifi或以太网连接的普通PC或笔记本电脑组成。在这项工作中，测试了添加新PC时分布式进化算法如何达到解决方案的效果，该效果是否也转化为算法的算法性能。为此，使用建议的多计算机解决了不同（困难）的问题，分析了自动负载平衡和同步对算法成功速度的影响，并分析了当多计算机实现时每秒的评估数量如何增加-计算机包括新节点。用于分析的度量是每秒评估数，当多计算机包含新节点时，该评估数会增加。该算法解决了所提出的问题，并且可以在同构或异构平台上运行。为了检查与所选存储服务的几种信息交换速率的算法结果，该实验包括两个问题和分布式进化算法的不同配置。结果表明，该系统在同构或异构节点上都是可行的，并且对于我们测试的同步存储服务没有显着差异。但是，当问题更加棘手时，算法的线程并不会因每次信息交换而停止（个人从一个人群到另一个人群的迁移），因此使用特定服务的区别对于算法的成功意义重大。

著录项

  • 来源
    《Natural Computing》 |2013年第2期|135-147|共13页
  • 作者

    K. Meri; M. G. Arenas; A. M. Mora; J. J. Merelo; P. A. Castillo; P. Garcia-Sanchez; J. L. J. Laredo;

  • 作者单位

    GeNeura Department of Architecture and Computer Technology,ETSIIT-CITIC,University of Granada,Granada,Spain;

    GeNeura Department of Architecture and Computer Technology,ETSIIT-CITIC,University of Granada,Granada,Spain;

    GeNeura Department of Architecture and Computer Technology,ETSIIT-CITIC,University of Granada,Granada,Spain;

    GeNeura Department of Architecture and Computer Technology,ETSIIT-CITIC,University of Granada,Granada,Spain;

    GeNeura Department of Architecture and Computer Technology,ETSIIT-CITIC,University of Granada,Granada,Spain;

    GeNeura Department of Architecture and Computer Technology,ETSIIT-CITIC,University of Granada,Granada,Spain;

    GeNeura Department of Architecture and Computer Technology,ETSIIT-CITIC,University of Granada,Granada,Spain;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Evolutionary parallel algorithm; Cloud computing; Free storage services; Distributed computing;

    机译：进化并行算法;云计算;免费存储服务;分布式计算;

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