TrimCaching: Parameter-Sharing AI Model Caching in Wireless Edge Networks

Next-generation mobile networks are expected to facilitate fast AI model downloading to end users. By caching models on edge servers, mobile networks can deliver models to end users with low latency, resulting in a paradigm called edge model caching. In this paper, we develop a novel model placement...

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Bibliographic Details

Published in:	Proceedings of the International Conference on Distributed Computing Systems pp. 36 - 46
Main Authors:	Qu, Guanqiao, Lin, Zheng, Liu, Fangming, Chen, Xianhao, Huang, Kaibin
Format:	Conference Proceeding
Language:	English
Published:	IEEE 23.07.2024
Subjects:	Approximation algorithms Computational modeling Edge AI Edge AI model caching edge computing edge intelligence Greedy algorithms model downloading Servers Simulation Wireless networks
ISSN:	2575-8411
Online Access:	Get full text
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