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Compute-First Networking (Dagstuhl Seminar 21243)

  • A Dagstuhl seminar on Compute-First Networking (CFN) was held online from June 14th to June 16th 2021. We discussed the opportunities and research challenges for a new approach to in-network computing, which aims to overcome limitations of traditional edge/in-network computing systems. The seminar discussed relevant use cases such as privacy-preserving edge video processing, connected and automated driving, and distributed health applications leveraging federated machine learning. A discussion of research challenges included an assessment of recent and expected future developments in networking and computing platforms and the consequences for in-network computing as well as an analysis of hard problems in current edge computing architectures. We exchanged ideas on a variety of research topics and about the results of corresponding activities in the larger fields of distributed computing and network data plane programmability. We also discussed a set of suggested PhD topics and promising future research directions in the CFN space such as split learning that is supported by in-network computing.

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Metadaten
Author:Jon Crowcroft, Philip Eardley, Dirk KutscherORCiD, Eve M. Schooler
DOI:https://doi.org/10.4230/DagRep.11.5.54
Parent Title (English):Dagstuhl Reports; Dagstuhl Seminar on Compute-First Networking (CFN), 14.06.-16.06.2021, virtual
Document Type:Conference Proceeding
Language:English
Year of Completion:2021
Release Date:2025/02/25
Tag:Distributed Machine Learning; Distributed Systems; Edge-Computing; In-Network Computing; Networking
Volume:11
Issue:5
First Page:54
Last Page:57
Institute:Fachbereich Technik
Research Focus Area:Industrielle Informatik