  The existing computation and communication (2C) optimization schemes for
vehicular edge computing (VEC) networks mainly focus on the physical domain
without considering the influence from the social domain. This may greatly
limit the potential of task offloading, making it difficult to fully boom the
task offloading rate with given power, resulting in low energy efficiency (EE).
To address the issue, this letter devotes itself to investigate
social-mobility-aware VEC framework and proposes a novel EE-oriented 2C
assignment scheme. In doing so, we assume that the task vehicular user (T-VU)
can offload computation tasks to the service vehicular user (S-VU) and the road
side unit (RSU) by non-orthogonal multiple access (NOMA). An optimization
problem is formulated to jointly assign the 2C resources to maximize the system
EE, which turns out to be a mixed integer non-convex objective function. To
solve the problem, we transform it into separated computation and communication
resource allocation subproblems. Dealing with the first subproblem, we propose
a social-mobility-aware edge server selection and task splitting algorithm
(SM-SSTSA) to achieve edge server selection and task splitting. Then, by
solving the second subproblem, the power allocation and spectrum assignment
solutions are obtained utilizing a tightening lower bound method and a
Kuhn-Munkres algorithm. Finally, we solve the original problem through an
iterative method. Simulation results demonstrate the superior EE performance of
the proposed scheme.
