Distributed Artificial Intelligence Enabled by oneM2M and Fog Networking

Kun Luncai, Fuchun Josephlin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Deep learning enabled by neural networks has been proven to be an effective Artificial Intelligence (AI) algorithm in sophisticated applications. The algorithm is normally divided into two phases: learning phase and inference phase. In this research, we assume the learning phase is already accomplished offline and focus on expediting the inference phase by replacing the centralized processing of Cloud with the distributed processing of Fog. In our approach, inference algorithms in AI are distributed to multiple layers of Fog networking, constructed from oneM2M Middle Nodes. We verify the performance improvement of our proposed distributed AI/Fog system by comparing it against a Cloud-centric system based on a use case of smart shopping mall.

Original languageEnglish
Title of host publication2018 IEEE Conference on Standards for Communications and Networking, CSCN 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538681466
DOIs
StatePublished - 19 Dec 2018
Event2018 IEEE Conference on Standards for Communications and Networking, CSCN 2018 - Paris, France
Duration: 29 Oct 20181 Nov 2018

Publication series

Name2018 IEEE Conference on Standards for Communications and Networking, CSCN 2018

Conference

Conference2018 IEEE Conference on Standards for Communications and Networking, CSCN 2018
CountryFrance
CityParis
Period29/10/181/11/18

Keywords

  • Artificial Intelligence
  • Fog computing
  • IoT platform
  • OneM2M

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  • Cite this

    Luncai, K., & Josephlin, F. (2018). Distributed Artificial Intelligence Enabled by oneM2M and Fog Networking. In 2018 IEEE Conference on Standards for Communications and Networking, CSCN 2018 [8581775] (2018 IEEE Conference on Standards for Communications and Networking, CSCN 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSCN.2018.8581775