• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Wireless Communications and Mobile Computing Conference >Industrial Vision Optimization Distributed Strategy based on Edge Intelligence Collaboration
【24h】

Industrial Vision Optimization Distributed Strategy based on Edge Intelligence Collaboration

机译：基于边缘智能协作的工业视觉优化分布式策略

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper, it is proposed that a novel strategy of based hierarchical data distribution and deep neural networks distribution over edge and end devices. In the Industrial Internet of Things environment, deep learning tasks such as smoke and fire classification based on convolutional neural network usually need to be performed on edge servers and end devices, which have limited computing resources, while edge servers have abundant computing resources. While being able to accommodate inference of a deep neural network (DNN) at the edge server, a distributed deep neural network (DDNN) also allows localized inference using a portion of the neural network at the end sensing devices. Therefore, this article proposed the distributed strategy can dynamically adjust network layers and data allocation proportion of end devices and edge servers according to different tasks to shorten the data processing time. A joint optimization problem is proposed to minimize the total delay, which is affected by the complexity of the DL model, the inference error rate, the computing power of the end devices and the edge servers. An analytical solution of a closed solution is derived and an optimal distributed data allocation and neural network allocation algorithm is proposed
机译：在本文中，提出了一种基于分层数据分布的新策略和边缘设备的深度神经网络分布。在工业环境互联网环境中，基于卷积神经网络的烟雾和火灾分类等深度学习任务通常需要在边缘服务器和终端设备上执行，其具有有限的计算资源，而边缘服务器具有丰富的计算资源。虽然能够在边缘服务器处容纳深神经网络（DNN）的推断，但是分布式深度神经网络（DDNN）还允许在最终感测设备处使用一部分神经网络的局部推断。因此，本文提出了分布式策略可以根据不同的任务来动态调整终端设备和边缘服务器的网络层和数据分配比例，以缩短数据处理时间。提出了一个联合优化问题，以最小化受DL模型复杂性影响的总延迟，推理误差率，最终设备的计算能力和边缘服务器的影响。推导了封闭解决方案的分析解决方案，提出了最佳分布式数据分配和神经网络分配算法

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