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.
@Article{crowcroft_et_al:DagRep.11.5.54, author = {Crowcroft, Jon and Eardley, Philip and Kutscher, Dirk and Schooler, Eve M.}, title = {{Compute-First Networking (Dagstuhl Seminar 21243)}}, pages = {54--75}, journal = {Dagstuhl Reports}, ISSN = {2192-5283}, year = {2021}, volume = {11}, number = {5}, editor = {Crowcroft, Jon and Eardley, Philip and Kutscher, Dirk and Schooler, Eve M.}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.11.5.54}, URN = {urn:nbn:de:0030-drops-155706}, doi = {10.4230/DagRep.11.5.54}, annote = {Keywords: Distributed Machine Learning, distributed systems, edge-computing, in-network computing, networking} }