Mitsubishi Electric Research Laboratories, Inc.

Ferdous Pervej

Philip Orlik

Stefano Di Cairano

Kieran Parsons

Jianlin Guo

Karl Berntorp

Marcel Menner

Kyeong-Jin Kim

A computer-implemented method is provided for training a global machine learning model using a learning server and a set of vehicle agents connected to roadside units (RSUs). It involves selecting agents, associating them with RSUs based on proximity, and transmitting training data and deadlines. Agents train models locally, which are then aggregated through RSUs to refine the global model to desired precision. The method includes steps of selecting vehicle agents from a pool of the vehicle agents connected to the RSUs, associating the selected vehicle agents and the RSUs respectively based on distances from the selected vehicle agents to the RSUs configured to provide measurements of the distances to the learning server, and transmitting a global model, a selected agent set and deadline thresholds in each global training round to the RSUs configured to transmit the global model and training deadlines to the selected vehicle agents.

Communication and computation aware distributed machine learning for vehicular networks

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Raleigh, NC, United States of America

Ferdous Pervej