A Data-Driven Platform for Capacity and Resource Management in Vehicular Fog Computing

Project Details

Description

Internet of things for automotive lets us enjoy a better in-car experience, and drives innovation of vehicular applications towards safer and more efficient transportation. This project focuses on solving the fundamental challenges of providing reliable and cost-effective fog computing services for the emerging vehicular applications that involve large-scale data-intensive crowdsensing and intelligent sensor fusion. Our proposal is vehicular fog computing, an innovative paradigm that brings computing power to the edge of the cellular network, and to predictably-routed commercial fleets like buses and taxis. The aim of this project is to develop a data-driven platform for effective capacity and resource management in vehicular fog computing. The expected outcomes will provide new insights on the design, implementation and deployment of vehicular fog computing.
Short titleDataFog
AcronymDataFog
StatusActive
Effective start/end date01/01/201931/12/2022
  • Best Paper Award

    Xiao, Yu (Recipient), Nov 2019

    Prize: Award or honor granted for a specific work