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...

Celý popis

Podrobná bibliografia

Vydané v:	Proceedings of the International Conference on Distributed Computing Systems s. 36 - 46
Hlavní autori:	Qu, Guanqiao, Lin, Zheng, Liu, Fangming, Chen, Xianhao, Huang, Kaibin
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 23.07.2024
Predmet:	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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!