  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.
