ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2020, Vol. 57 ›› Issue (9): 1800-1809.doi: 10.7544/issn1000-1239.2020.20200253

Special Issue: 2020边缘计算专题

Previous Articles     Next Articles

Edge Computing in Smart Homes

Huang Qianyi1,2, Li Zhiyang3, Xie Wentao3, Zhang Qian3   

  1. 1(Institute of Future Networks, Southern University of Science and Technology, Shenzhen, Guangdong 518055);2(Peng Cheng Laboratory, Shenzhen, Guangdong 518055);3(Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong 999077)
  • Online:2020-09-01
  • Supported by: 
    This work was supported by RGC General Research Fund (CERG 16204418, 16203719, FP909, R8015), the National Natural Science Foundation of China (61872420), the Natural Science Foundation of Guangdong Province (2017A030312008), the Key-Area Research and Development Program of Guangdong Province (2019B121204009), and the Project of “FANet: PCL Future Greater-Bay Area Network Facilities for Large-scale Experiments and Applications” (LZC0019).

Abstract: In recent years, smart speakers and robotic vacuum cleaners have played important roles in many peoples daily life. With the development in technology, more and more intelligent devices will become parts of home infrastructure, making life more convenient and comfortable for residents. When different types of specialized intelligent devices are connected and operated over the Internet, how to minimize network latency and guarantee data privacy are open issues. In order to solve these problems, edge computing in smart homes becomes the future trend. In this article, we present our research work along this direction, covering the topics on edge sensing, communication and computation. As for sensing, we focus on the pervasive sensing capability of the edge node and present our work on contactless breath monitoring; as for communication, we work on the joint design of sensing and communication, so that sensing and communication systems can work harmoniously on limited spectrum resources; as for computation, we devote our efforts to personalized machine learning at the edge, building personalized model for each individual while guaranteeing their data privacy.

Key words: edge computing, smart home, Internet-of-Things, ubiquitous sensing, federated learning

CLC Number: