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EdgeFlow: Open-Source Multi-layer Data Flow Processing in Edge Computing for 5G and Beyond

机译：EdgeFlow：边缘计算的开源多层数据流处理5G及更高

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摘要

Edge computing has evolved to be a promising avenue to enhance system computing capability by offloading processing tasks from the cloud to edge devices. In this article, we propose a multi-layer edge computing framework called EdgeFlow. In this framework, different nodes ranging from edge devices to cloud data centers are categorized into corresponding layers and cooperate for data processing. EdgeFlow can deal with the trade-off between the computing and communication capabilities so that the tasks can be assigned to each layer optimally. At the same time, resources are carefully allocated throughout the whole network to mitigate performance fluctuation. The proposed open-source data flow processing framework is implemented on a platform that can emulate various computing nodes in multiple layers and corresponding network connections. Evaluated on the face recognition scenario, EdgeFlow can significantly reduce task finish time and perform more tolerance to run-time variations, compared with pure cloud computing, pure edge computing, and Cloudlet. Potential applications of EdgeFlow, including network function virtualization, Internet of Things, and vehicular networks, are also discussed at the end of this article.
机译：边缘计算已经发展为一个有希望的途径，通过将处理任务从云卸载到边缘设备来增强系统计算能力。在本文中，我们提出了一个名为EdgeFlow的多层边缘计算框架。在该框架中，从边缘设备到云数据中心的不同节点分类为相应的层并配合数据处理。 EdgeFlow可以处理计算和通信功能之间的权衡，以便可以最佳地分配给每个图层的任务。与此同时，资源在整个网络中仔细分配以减轻性能波动。所提出的开源数据流处理框架在平台上实现，该平台可以在多层中模拟各种计算节点和相应的网络连接。对面部识别方案进行评估，边缘流可以显着降低任务完成时间并对运行时变化执行更容忍，与纯云计算，纯边沿计算和Cloudlet相比。在本文结束时还讨论了EdgeFlow的潜在应用，包括网络功能虚拟化，事物和车辆网络。

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  • 来源
    《IEEE Network》 |2019年第2期|166-173|共8页
  • 作者

    Yao Chao; Wang Xiaoyang; Zheng Zijie; Sun Guangyu; Song Lingyang;

  • 作者单位

    Peking Univ Sch Elect Engn & Comp Sci Beijing Peoples R China;

    Peking Univ Beijing Peoples R China;

    Peking Univ Sch Elect Engn & Comp Sci Beijing Peoples R China;

    Peking Univ CECA Beijing Peoples R China;

    Peking Univ Sch Elect Engn & Comp Sci Beijing Peoples R China;

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