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

  • Xiao, Yu (Principal investigator)
  • Akgul, Özgür (Project Member)
  • Zhanabatyrova, Aziza (Project Member)
  • Zhu, Chao (Project Member)
  • Cho, Byung (Project Member)
  • Mao, Wencan (Project Member)
  • Noreikis, Marius (Project Member)
  • Li, Xuebing (Project Member)

Project Details


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.
Effective start/end date01/01/201931/12/2022

Collaborative partners

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 7 - Affordable and Clean Energy
  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 11 - Sustainable Cities and Communities


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
  • Best Paper Award

    Xiao, Yu (Recipient), Nov 2019

    Prize: Award or honor granted for a specific work