Distributed Artificial Intelligence Enabled by oneM2M and Fog Networking

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.

[1]  H. T. Kung,et al.  Distributed Deep Neural Networks Over the Cloud, the Edge and End Devices , 2017, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS).

[2]  Monika Jhuria,et al.  Image processing for smart farming: Detection of disease and fruit grading , 2013, 2013 IEEE Second International Conference on Image Information Processing (ICIIP-2013).

[3]  Foster J. Provost,et al.  Scaling Up: Distributed Machine Learning with Cooperation , 1996, AAAI/IAAI, Vol. 1.

[4]  Tao Zhang,et al.  Fog and IoT: An Overview of Research Opportunities , 2016, IEEE Internet of Things Journal.

[5]  Zheng Zhang,et al.  MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems , 2015, ArXiv.

[6]  Haibo He,et al.  A Hierarchical Distributed Fog Computing Architecture for Big Data Analysis in Smart Cities , 2015, ASE BD&SI.

[7]  Kin K. Leung,et al.  When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications.

[8]  Christian Bonnet,et al.  A lightweight framework for efficient M2M device management in oneM2M architecture , 2015, 2015 International Conference on Recent Advances in Internet of Things (RIoT).

[9]  J. Li,et al.  Smart city and the applications , 2011, 2011 International Conference on Electronics, Communications and Control (ICECC).

[10]  Massimo Satler,et al.  Towards Smart Farming and Sustainable Agriculture with Drones , 2015, 2015 International Conference on Intelligent Environments.