Topology-Aware Dynamic Computation Offloading in Vehicular Networks

Driven by the tremendous in vehicular networks computation-intensive application demands, the incorporation of mobile edge computing (MEC) and vehicular cloud is convinced as a promising paradigm to fulfill computation offloading requirements. However, the changing vehicular communication topology (CVCT) poses a significant challenge for offloading directed acyclic graph (DAG) model application. Due to the precedence and connection constraint between different sub-jobs, the successful offloading of DAG-enabled apllication will be disturbed even interrupted without considering CVCT. To address this problem, we propose a topology-aware dynamic computaion offloading mechanism and adopt simulated annealing algorithm (TASA) to jointly optimize the energy consumption and completion time under dynamic environment, while guaranteeing the convergence of the proposed method. Simulation results reveal the effectiveness of the proposed method in overcoming CVCT's influence.

Automated summary

Driven by the increasing demands of computation-intensive application in vehicular networks, the integration of mobile edge computing (MEC) and vehicular cloud is seen as a promising solution. However, the changing vehicular communication topology (CVCT) poses challenges for offloading directed acyclic graph (DAG) model application. A new topology-aware dynamic computation offloading mechanism using simulated annealing algorithm (TASA) has been proposed to optimize energy consumption and completion time while overcoming the influence of CVCT.