基于移动边缘计算的车联网任务卸载研究与仿真

Research and Simulation of Internet of Vehicles Task Offloading Based on Mobile Edge Computing

为能够在接近用户端利用边缘设备的计算资源为人们提供高质量的服务,基于移动边缘计算的车联网架构设计了一种联合资源分配和任务卸载的机制。将原问题分解为资源分配和卸载决策2个子问题分别求解。将原问题简化成系统容量最大化的资源分配问题,通过比例资源分配算法得到初始卸载集合;采用联合卸载决策与资源分配机制求解上述问题。通过迭代直到实验现象趋于平稳。仿真结果表明:与以往方法相比该机制降低了算法的复杂度,并且用户效用始终较高,大大提升了车联网系统的服务效率。

In order to use the computing resources of edge devices to provide high-quality services,a joint resource allocation and task offloading mechanism is designed for the Internet of Vehicles architecture based on mobile edge computing.In the mechanism,the original problem is decomposed into two sub-problems of resource allocation and offloading decision.The original problem is simplified into the resource allocation of maximizing system capacity,and the initial offloading set is obtained through the proportional resource allocation algorithm;the above problem is solved by the joint offloading decision-making and resource allocation mechanism.The stable experimental results are obtained by iteration.The simulation results show that,compared with the previous methods,the mechanism reduces the complexity of the algorithm,and the user utility is always high,which greatly improves the service efficiency of the Internet of Vehicles system.