Distributed Artificial Intelligence Empowered by End-Edge-Cloud Computing: A Survey

Duan, Sijing; Wang, Dan; Ren, Ju; Lyu, Feng; Zhang, Ye; Wu, Huaqing; Shen, Xuemin

doi:10.1109/comst.2022.3218527

articleIEEE Communications Surveys & TutorialsNov 4, 2022Closed access

Distributed Artificial Intelligence Empowered by End-Edge-Cloud Computing: A Survey

SDSijing Duan DWDan Wang JRJu Ren FLFeng Lyu YZYe Zhang

Central South University · Tsinghua University · +3 more institutions

Indexed incrossref

Abstract

As the computing paradigm shifts from cloud computing to end-edge-cloud computing, it also supports artificial intelligence evolving from a centralized manner to a distributed one. In this paper, we provide a comprehensive survey on the distributed artificial intelligence (DAI) empowered by end-edge-cloud computing (EECC), where the heterogeneous capabilities of on-device computing, edge computing, and cloud computing are orchestrated to satisfy the diverse requirements raised by resource-intensive and distributed AI computation. Particularly, we first introduce several mainstream computing paradigms and the benefits of the EECC paradigm in supporting distributed AI, as well as the fundamental technologies for…

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359

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Percentile: 100%
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Topics

Keywords

Cloud computing
Computer science
Edge computing
Data science
Distributed computing
Utility computing
Cloud computing security
Artificial intelligence

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