  Task offloading in Internet of Vehicles (IoV) involves numerous steps and
optimization variables such as: where to offload tasks, how to allocate
computation resources, how to adjust offloading ratio and transmit power for
offloading, and such optimization variables and hybrid combination features are
highly coupled with each other. Thus, this is a fully challenge issue to
optimize these variables for task offloading to sustainably reduce energy
consumption with load balancing while ensuring that a task is completed before
its deadline. In this paper, we first provide a Mixed Integer Nonlinear
Programming Problem (MINLP) formulation for such task offloading under energy
and deadline constraints in IoV. Furthermore, in order to efficiently solve the
formulated MINLP, we decompose it into two subproblems, and design a
low-complexity Joint Optimization for Energy Consumption and Task Processing
Delay (JOET) algorithm to optimize selection decisions, resource allocation,
offloading ratio and transmit power adjustment. We carry out extensive
simulation experiments to validate JOET. Simulation results demonstrate that
JOET outperforms many representative existing approaches in quickly converge
and effectively reduce energy consumption and delay. Specifically, average
energy consumption and task processing delay have been reduced by 15.93% and
15.78%, respectively, and load balancing efficiency has increased by 10.20%.
