Edge-Cloud Polarization and Collaboration: A Comprehensive Survey
- URL: http://arxiv.org/abs/2111.06061v2
- Date: Fri, 12 Nov 2021 15:10:56 GMT
- Title: Edge-Cloud Polarization and Collaboration: A Comprehensive Survey
- Authors: Jiangchao Yao, Shengyu Zhang, Yang Yao, Feng Wang, Jianxin Ma, Jianwei
Zhang, Yunfei Chu, Luo Ji, Kunyang Jia, Tao Shen, Anpeng Wu, Fengda Zhang,
Ziqi Tan, Kun Kuang, Chao Wu, Fei Wu, Jingren Zhou, Hongxia Yang
- Abstract summary: We conduct a systematic review for both cloud and edge AI.
We are the first to set up the collaborative learning mechanism for cloud and edge modeling.
We discuss potentials and practical experiences of some on-going advanced edge AI topics.
- Score: 61.05059817550049
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Influenced by the great success of deep learning via cloud computing and the
rapid development of edge chips, research in artificial intelligence (AI) has
shifted to both of the computing paradigms, i.e., cloud computing and edge
computing. In recent years, we have witnessed significant progress in
developing more advanced AI models on cloud servers that surpass traditional
deep learning models owing to model innovations (e.g., Transformers, Pretrained
families), explosion of training data and soaring computing capabilities.
However, edge computing, especially edge and cloud collaborative computing, are
still in its infancy to announce their success due to the resource-constrained
IoT scenarios with very limited algorithms deployed. In this survey, we conduct
a systematic review for both cloud and edge AI. Specifically, we are the first
to set up the collaborative learning mechanism for cloud and edge modeling with
a thorough review of the architectures that enable such mechanism. We also
discuss potentials and practical experiences of some on-going advanced edge AI
topics including pretraining models, graph neural networks and reinforcement
learning. Finally, we discuss the promising directions and challenges in this
field.
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