Vehicular Computation Offloading for Industrial Mobile Edge Computing

Due to the limited local computation resource, industrial vehicular requires offloading tasks with time-delay sensitive and complex demands other intelligent devices (IDs) once data is sensed collected collaboratively. This article considers partial of vehicles (IVs) multiple available IDs mobile edge computing (MEC), including unmanned aerial (UAVs), fixed-position MEC servers, optimize system cost execution time, energy consumption, ID rental price. Moreover, increase access probability IV by UAVs, geographical area divided into small partitions schedule UAVs regarding regional density dynamically. A minimum incremental task allocation algorithm proposed divide whole assign units for increment each time. Experimental results show solution can significantly reduce cost.