Rising Stars 2020:

Tayebeh Bahreini

PhD Candidate

Wayne State University, Michigan

Areas of Interest

  • Distributed Systems
  • Edge Computing
  • Combinatorial Optimization


VECMAN: A Framework for Energy-Aware Resource Management in VEC Systems


In Vehicular Edge Computing (VEC) systems, the computing resources of connected Electric Vehicles (EV) are used to fulfill the low-latency computation requirements of vehicles. However, local execution of heavy workloads may drain a considerable amount of energy in EVs. One promising way to improve the energy efficiency is to share and coordinate computing resources among connected EVs. However, the uncertainties in the future location of vehicles make it hard to decide which vehicles participate in resource sharing and how long they share their resources so that all participants benefit from resource sharing.

In this research, we propose a framework for energy-aware resource management in VEC systems composed of two algorithms: (i) a resource selector algorithm that determines the participating vehicles and the duration of resource sharing period; and (ii) an energy manager algorithm that manages computing resources of the participating vehicles with the aim of minimizing the computational energy consumption. We evaluate the proposed framework and show that it considerably reduces the vehicles’ computational energy consumption compared to the state-of-the-art baselines. Specifically, our framework achieves 22-76% energy savings compared to a baseline that executes workload locally and an average of 25% energy savings compared to a baseline that offloads vehicles’ workloads to RSUs.


I am a Ph.D candidate in computer science at Wayne State University. I received the B.Sc. degree in computer science from University of Isfahan, Iran, in 2010, and the M.Sc. in computer engineering from Shahed University, Iran, in 2014. My main research interests are distributed systems, approximation algorithms, parallel computing, Electric Vehicles, and game theory. I am a student member of the ACM, IEEE, and INFORMS.

Personal home page