  Software-defined internet of vehicles (SDIoV) has emerged as a promising
paradigm to realize flexible and comprehensive resource management, for next
generation automobile transportation systems. In this paper, a vehicular cloud
computing-based SDIoV framework is studied wherein the joint allocation of
transmission power and graph job is formulated as a nonlinear integer
programming problem. To effectively address the problem, a
structure-preservation-based two-stage allocation scheme is proposed that
decouples template searching from power allocation. Specifically, a
hierarchical tree-based random subgraph isomorphism mechanism is applied in the
first stage by identifying potential mappings (templates) between the
components of graph jobs and service providers. A structure-preserving
simulated annealing-based power allocation algorithm is adopted in the second
stage to achieve the trade-off between the job completion time and energy
consumption. Extensive simulations are conducted to verify the performance of
the proposed algorithms.
