...
首页> 外文期刊>Expert systems with applications >A study of the contribution made by evolutionary learning on dynamic load-balancing problems in distributed computing systems
【24h】

A study of the contribution made by evolutionary learning on dynamic load-balancing problems in distributed computing systems

机译:进化学习对分布式计算系统中动态负载平衡问题的贡献的研究

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

A computer simulation model that investigated the contribution made by evolutionary learning techniques on load-balancing problems was proposed. Three parameters for controlling the load-balancing activity of a node were used. The system was tested in different distributed systems, including different processing and communication speeds as well as network structures. Our experimental results showed that the system demonstrated an effective learning capability in balancing load among different processing nodes. It also showed that each of these three parameters played an important role in contributing to load-balancing, and that the system performance increased upon increasing the number of parameter changes simultaneously. The contribution made by evolutionary learning was significant as the variety of node processing speeds increased.
机译:提出了一种计算机仿真模型,该模型研究了进化学习技术对负载均衡问题的贡献。使用了三个参数来控制节点的负载平衡活动。该系统在不同的分布式系统中进行了测试,包括不同的处理和通信速度以及网络结构。我们的实验结果表明,该系统在平衡不同处理节点之间的负载方面显示出有效的学习能力。它还表明,这三个参数中的每一个在促进负载平衡方面都起着重要作用,并且随着同时增加参数更改的数量,系统性能也会提高。随着节点处理速度的增加,进化学习做出的贡献是巨大的。

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