Proposing a framework for evaluating learning strategies in vehicular CPSs
Paper in proceeding, 2022

Highly-connected Vehicular Cyber-Physical Systems (VCPSs) offer manifold opportunities for distributing learning across the contained vehicles, road-side units and servers. However, simulating and evaluating particular distributed learning schemes poses a difficult problem in requiring realistic modeling of the vehicular fleet, communication, and the learning itself. In this work, we postulate a set of requirements for a framework simulating a complete learning workflow in a VCPS, and propose a modular architecture for it. Using a prototype implementation, we show with an example experiment the capabilities the proposed framework delivers for evaluating novel learning schemes in custom scenarios.

Fedrated learning

connected vehicle

Author

Bastian Havers

Network and Systems

Volvo Cars

Marina Papatriantafilou

Network and Systems

Ashok Krishna Chaitanya Koppisetty

Volvo Cars

Vincenzo Massimiliano Gulisano

Network and Systems

Middleware 2022 Industrial Track - Proceedings of the 23rd International Middleware Conference Industrial Track, Part of Middleware 2022

22-28
978-1-4503-9917-3 (ISBN)

23rd International Middleware Conference
Quebec City, Canada,

AUTOSPADA (Automotive Stream Processing and Distributed Analytics) OODIDA Phase 2

VINNOVA (2019-05884), 2020-03-12 -- 2022-12-31.

Subject Categories

Other Computer and Information Science

Information Science

Computer Science

Areas of Advance

Information and Communication Technology

Transport

DOI

10.1145/3564695.3564775

ISBN

9781450399173

More information

Latest update

10/27/2023