Slicing-Based Offloading in Vehicular Edge Computing

Abstract

Vehicular edge computing (VEC) provides an environment for offloading tasks from vehicles. Indeed, the advantage through VEC is to push power computational and storage capacities at the edge nodes near the vehicles to handle the enormous resources required by some applications. On the other hand, in order to manage efficiently these resources, it would be necessary to partition them into several parts, each dedicated to a specific service. Thus, integrating network slicing in VEC appears to be relevant. Therefore, in this paper we study the task offloading problem from vehicles to wireless 5G new generation nodes (gNBs) and road side units (RSUs) hosting sliced edge computing servers. We formulate the problem as an integer linear programming problem and propose a new algorithm, which follows a centralized control strategy to holistically view and manage the whole network, and the sliced edge nodes. In addition, it follows network function virtualization framework to separate the logical network from the physical resources. The simulation results show that, in terms of acceptance ratio, the proposed algorithm provides very close results to the optimal solution, and when compared to state-of-art algorithm, integrating slicing is better when there is enough resources on the hosting nodes, but it still guarantees the differentiation among services.