Decentralized Edge Intelligence: A Dynamic Resource Allocation Framework for Hierarchical Federated Learning

To enable the large scale and efficient deployment of Artificial Intelligence (AI), the confluence of AI and Edge Computing has given rise to Edge Intelligence, which leverages on the computation and communication capabilities of end devices and edge servers to process data closer to where it is pro...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on parallel and distributed systems Ročník 33; číslo 3; s. 536 - 550
Hlavní autoři:	Lim, Wei Yang Bryan, Ng, Jer Shyuan, Xiong, Zehui, Jin, Jiangming, Zhang, Yang, Niyato, Dusit, Leung, Cyril, Miao, Chunyan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.03.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Artificial intelligence auction Clusters Computational modeling Data models Deep learning Edge computing edge intelligence evolutionary game Federated learning Game theory Games Machine learning Magnetic heads Performance evaluation Resource allocation Resource management Servers Stability analysis Training
ISSN:	1045-9219, 1558-2183
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!