本研究室「HuangLab @ SYSU」关于“智能边缘计算 (Intelligent Edge Computing)”的两篇研究论文分别被 IEEE Communications Magazine（影响因子10.356，中科院一区） 与 IEEE Internet of Things Journal （影响因子9.5，中科院一区） 接收。两篇论文，本人均为通讯作者。

   论文的题目分别是：

1. "Real-Time Fault-Detection for IIoT Facilities using GBRBM-based DNN"  (下载链接)

2. "Machine Fault Detection for Intelligent Self-Driving Networks" (下载链接)

   在这两篇论文里，我们旨在为边缘计算构建一种称为“自驱动网络（Self-Driving Networks, SelfDN）”的机制。该机制主要应用智能算法来减轻人类管理员对网络的干预，让边缘计算网络可以实现“自发现、自决策、自配置 与 自恢复”的闭环网络优化。可见，智能算法在“自驱动网络”架构里起着感知发现、推理、决策等重要作用。

   目前我们暂且只对“发现”这一环节做出了初步探索，并以工业物联网（IIoT）为边缘计算的应用场景来展示机器故障的“探测发现”过程。其他环节里的更多科学问题，还有待后续的更多研究者来参与进来并提出解决方案。

 

    两篇论文使用的用于预测数据中心服务器故障的数据集，以及数据处理代码，请从研究室 HuangLab 的【Datasets】页面下载：http://xintelligence.pro/datasets

 

黄华威

中山大学，软件工程学院

 

[English Version]

Dear Colleagues,

Glad to see that our paper entitled "Real-Time Fault-Detection for IIoT Facilities using GBRBM-based DNN"  (URL) has been online published by hashtagIEEE Internet of Things Journal (SCI hashtagIF=9.5). This work is a showcase of continuous intelligence ‍‍in "Self-Driving" Networks.hashtag

 

  Another paper entitled "Machine Fault Detection for Intelligent Self-Driving Networks" (URL) has been accepted by IEEE Communications Magazine (SCI IF= 10.356). We expect that this article can inspire booming studies of Self-Driving Networks (SelfDN).

 

  By the way, SelfDN is an emerging networking paradigm that advocates the self-discovery, self-analysis, self-configuration, and self-correction in the target networks without human intervention.

 

  Please refer to more details from my project log -> [URL]

   Please feel free to download the datasets and the processing codes from the [Datasets] page of X-Intelligence Lab: http://xintelligence.pro/datasets  

 

Thank you for your attention!

 

Best regards,

 

Huawei Huang,

Associate Professor,

SSE, Sun Yat-sen University, China