Artificial Intelligence for Internet of Things as a Service: Small or Big Data, Private or Public Model, Centralized or Federated Learning?

Ying Dar Lin; Yuan Cheng Lai; Didik Sudyana; Ren Hung Hwang

doi:10.1109/MC.2023.3303370

Artificial Intelligence for Internet of Things as a Service: Small or Big Data, Private or Public Model, Centralized or Federated Learning?

Ying Dar Lin
, Yuan Cheng Lai
, Didik Sudyana^*
, Ren Hung Hwang

^*此作品的通信作者

研究成果: Article

4 引文斯高帕斯（Scopus）

摘要

We propose a generic framework for mapping the training and federation tasks of three artificial intelligence for Internet of Things as a service (AIoTaS) systems to multiple cloud-fog paradigms. A total of 31 possible mappings are identified as possible reference designs for AIoTaS providers.

原文	English
頁面	65-79
頁數	15
卷	56
無	12
專業出版物	Computer
DOIs	https://doi.org/10.1109/MC.2023.3303370
出版狀態	Published - 1 12月 2023

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10.1109/MC.2023.3303370

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title = "Artificial Intelligence for Internet of Things as a Service: Small or Big Data, Private or Public Model, Centralized or Federated Learning?",

abstract = "We propose a generic framework for mapping the training and federation tasks of three artificial intelligence for Internet of Things as a service (AIoTaS) systems to multiple cloud-fog paradigms. A total of 31 possible mappings are identified as possible reference designs for AIoTaS providers.",

author = "Lin, \{Ying Dar\} and Lai, \{Yuan Cheng\} and Didik Sudyana and Hwang, \{Ren Hung\}",

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AU - Hwang, Ren Hung

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AB - We propose a generic framework for mapping the training and federation tasks of three artificial intelligence for Internet of Things as a service (AIoTaS) systems to multiple cloud-fog paradigms. A total of 31 possible mappings are identified as possible reference designs for AIoTaS providers.

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U2 - 10.1109/MC.2023.3303370

DO - 10.1109/MC.2023.3303370

M3 - Article

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JO - Computer

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Artificial Intelligence for Internet of Things as a Service: Small or Big Data, Private or Public Model, Centralized or Federated Learning?

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