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

計算機與網路中心

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 - 2023 12月 1

All Science Journal Classification (ASJC) codes

一般電腦科學

存取文件

10.1109/MC.2023.3303370

其它文件與鏈接

引用此

@misc{f0d3e0e203214d3996a5162d68064ed4,

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\}",

note = "Publisher Copyright: {\textcopyright} 1970-2012 IEEE.",

year = "2023",

month = dec,

day = "1",

doi = "10.1109/MC.2023.3303370",

language = "English",

volume = "56",

pages = "65--79",

journal = "Computer",

issn = "0018-9162",

publisher = "IEEE Computer Society",

}

TY - GEN

T1 - Artificial Intelligence for Internet of Things as a Service

T2 - Small or Big Data, Private or Public Model, Centralized or Federated Learning?

AU - Lin, Ying Dar

AU - Lai, Yuan Cheng

AU - Sudyana, Didik

AU - Hwang, Ren Hung

PY - 2023/12/1

Y1 - 2023/12/1

N2 - 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.

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.

UR - https://www.scopus.com/pages/publications/85177856614

UR - https://www.scopus.com/pages/publications/85177856614#tab=citedBy

U2 - 10.1109/MC.2023.3303370

DO - 10.1109/MC.2023.3303370

M3 - Article

AN - SCOPUS:85177856614

SN - 0018-9162

VL - 56

SP - 65

EP - 79

JO - Computer

JF - Computer

ER -

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

摘要

All Science Journal Classification (ASJC) codes

存取文件

其它文件與鏈接

指紋

引用此