Hybrid Vehicular and Cloud Distributed Computing

In this study, we propose the use of hybrid offloading of computing tasks simultaneously to edge servers (vertical offloading) via LTE communication and to nearby cars (horizontal offloading) via V2V communication, in order to increase the rate at which tasks are processed compared to local processing. Horizontal offloading is enabled by the vehicle cloudification framework, a paradigm that involves forming virtual cloud servers from vehicles in proximity of each other on the road, known as vehicular micro clouds.

Our main focus is developing an optimized resource assignment and scheduling framework for hybrid offloading of computing tasks. The design goal is to optimally utilize the computational resources in the edge and in the vehicular micro cloud, while taking into account communication constraints and task requirements.

Staff:

  • Principal Investigator: Danijela Cabric
  • Students: Enes Krijestorac, Ghaith Hattab

Selected publications:

E. Krijestorac, A. Memedi, T. Higuchi, S. Ucar, O. Altintas, D. Cabric, "Hybrid Vehicular and Cloud Distributed Computing: A Case for Cooperative Perception", to appear IEEE Globecom 2020, May 2020.
IoTDistributed computing
G. Hattab, S. Ucar, T. Higuchi, O. Altintas, F. Dressler, and D. Cabric, “Optimized Assignment of Computational Tasks in Vehicular Micro Clouds”, to appear in Int. Workshop on Edge Systems, Analytics and Networking (EdgeSys’19), Feb. 2019.