  Modern vehicles equipped with on-board units (OBU) are playing an essential
role in the smart city revolution. The vehicular processing resources, however,
are not used to their fullest potential. The concept of vehicular clouds is
proposed to exploit the underutilized vehicular resources to supplement cloud
computing services to relieve the burden on cloud data centers and improve
quality of service. In this paper we introduce a vehicular cloud architecture
supported by fixed edge computing nodes and the central cloud. A mixed integer
linear programming (MLP) model is developed to optimize the allocation of the
computing demands in the distributed architecture while minimizing power
consumption. The results show power savings as high as 84% over processing in
the conventional cloud. A heuristic with performance approaching that of the
MILP model is developed to allocate computing demands in real time.
