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Software Defined Networking in Advanced Manufacturing Systems

机译:先进制造系统中的软件定义网络

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摘要

Robots have been widely used in industry to reduce the risk of severe injuries to human operators. Robots can operate using either local or remote (in the Cloud) computing re-sources. The latter case has several advantages over the former, including resource sharing, cost effectiveness, ease of maintenance, and scalability. In a typical scenario, data sensed by or for the robot need to be quickly and reliably transferred to one or more remote servers for further processing. Particularly important to the application is to rely on a reliable connection between the robot/sensor and the remote server.;In order to guarantee uninterrupted data transmission even in the presence of network out-ages, the development and adoption of new technologies such as high-speed flexible networks employing software-defined networking (SDN) technology are of the essence to flexibly interconnect the production floor to the cloud sites.;Firstly, we studied and found that when the CPU, memory, and network bandwidth resources that are allocated in the two environments (LAN vs WAN) are comparable, the execution time of the Godel software in the LAN and WAN environment does not differ significantly. Secondly, we proposed the PROnet Orchestrator, a SDN-based two-layer orchestrator software platform. The PROnet Orchestrator is designed to provision and maintenance end-to-end Ethernet flows through optical network. Finally, we ran industrial robot application over PROnet, and the experimental results demonstrated that the self-healing and prompt response of the Ethernet layer prevent a ROS-I application from being disrupted.
机译:机器人已在工业中广泛使用,以减少对操作人员造成严重伤害的风险。机器人可以使用本地或远程(在云中)计算资源进行操作。后一种情况比前一种情况具有多个优点,包括资源共享,成本效益,易于维护和可伸缩性。在典型情况下,需要将机器人所感测到的数据快速可靠地传输到一个或多个远程服务器以进行进一步处理。对于应用程序而言,特别重要的是依靠机械手/传感器与远程服务器之间的可靠连接。;为了即使在网络中断的情况下也能确保不间断的数据传输,诸如新技术的开发和采用使用软件定义网络(SDN)技术的高速灵活网络对于将生产车间灵活地互连到云站点至关重要。首先,我们研究发现,当CPU,内存和网络带宽资源被分配到两种环境(LAN与WAN)具有可比性,因此Godel软件在LAN和WAN环境中的执行时间没有显着差异。其次,我们提出了PROnet Orchestrator,这是一个基于SDN的两层Orchestrator软件平台。 PROnet Orchestrator旨在通过光网络配置和维护端到端以太网流。最后,我们在PROnet上运行了工业机器人应用程序,实验结果表明,以太网层的自我修复和快速响应可以防止ROS-I应用程序被破坏。

著录项

  • 作者

    Shao, Chencheng.;

  • 作者单位

    The University of Texas at Dallas.;

  • 授予单位 The University of Texas at Dallas.;
  • 学科 Robotics.;Systems science.;Electrical engineering.
  • 学位 M.S.T.E.
  • 年度 2017
  • 页码 65 p.
  • 总页数 65
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 康复医学;
  • 关键词

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