# Energy Efficient and Delay Aware Vehicular Edge Cloud

arXiv: https://arxiv.org/abs/2004.07170 · HTML: https://mlsanity.com/paper/2004.07170/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Apr 2020.

## Built on by (most cited first, 1 of 1)

- [Learning Based Task Offloading in Digital Twin Empowered Internet of Vehicles](https://mlsanity.com/paper/2201.09076/) (2021)

## Abstract (arXiv)

Vehicular Edge Clouds (VECs) is a new distributed processing paradigm that exploits the revolution in the processing capabilities of vehicles to offer energy efficient services and improved QoS. In this paper we tackle the problem of processing allocation in a cloud-fog-VEC architecture by developing a joint optimization Mixed Integer Linear Programming (MILP) model to minimize power consumption, propagation delay, and queuing delay. The results show that while VEC processing can reduce the power consumption and propagation delay, VEC processing can increase the queuing delay because of the low data rate connectivity between the vehicles and the data source nodes.