首页> 外国专利> DETERMINE RECOVERY MECHANISM IN A STORAGE SYSTEM BY TRAINING A MACHINE LEARNING MODULE

DETERMINE RECOVERY MECHANISM IN A STORAGE SYSTEM BY TRAINING A MACHINE LEARNING MODULE

机译:通过训练机器学习模块来确定存储系统中的恢复机制

摘要

A machine learning module receives inputs comprising attributes of a storage controller, where the attributes affect failures that occur in the storage controller. In response to a failure occurring in the storage controller, a plurality of output values corresponding to a plurality of recovery mechanisms to recover from the failure in the storage controller are generated via forward propagation through a plurality of layers of the machine learning module. A margin of error is calculated based on comparing the generated output values to expected output values corresponding to the plurality of recovery mechanisms, where the expected output values are generated from an indication of a correct recovery mechanism for the failure. An adjustment is made of weights of links that interconnect nodes of the plurality of layers via back propagation to reduce the margin of error, to improve a determination of a recovery mechanism for the failure.
机译:机器学习模块接收包括存储控制器的属性的输入,其中这些属性影响在存储控制器中发生的故障。响应于在存储控制器中发生的故障,经由机器学习模块的多个层的正向传播,生成与从存储控制器的故障中恢复的多个恢复机制相对应的多个输出值。基于将生成的输出值与对应于多个恢复机制的期望输出值进行比较来计算误差容限,其中,期望输出值是从针对故障的正确恢复机制的指示中生成的。通过反向传播对使多层的节点互连的链路的权重进行调整,以减少错误余量,从而改善对故障的恢复机制的确定。

著录项

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

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