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Distributed Artificial Intelligence Enabled by oneM2M and Fog Networking

机译:由ONEM2M和FOG网络启用的分布式人工智能

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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.
机译:通过神经网络实现的深度学习已被证明是一种有效的人工智能(AI)算法在复杂的应用中。该算法通常分为两个阶段:学习阶段和推理阶段。在这项研究中,我们假设学习阶段已经离线完成,并专注于通过用雾的分布式处理替换云的集中处理来加速推理阶段。在我们的方法中,AI中的推理算法被分发到多个雾网络,由OneM2M中间节点构成。我们通过将其与智能购物商场的用例比较来验证我们提出的分布式AI / FOG系统的性能改进。

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