车载边缘计算中多任务部分卸载方案研究

Research on Multi-task Partial Offloading Scheme in Vehicular Edge Computing

现有车载应用设备对时延有更严苛的要求,车载边缘计算(VEC)能够充分利用网络边缘设备,如路边单元(RSU)进行协作处理,可有效地降低时延。现有研究多假设RSU计算资源充足,可提供无限的服务,但实际其计算资源会随着所需处理任务数量的增加而受限,对时延敏感的车载应用造成限制。该文针对此问题,提出一种车载边缘计算中多任务部分卸载方案,该方案在充分利用RSU的计算资源条件下,考虑邻近车辆的剩余可用计算资源,以最小化总任务处理时延。首先在时延限制和资源约束下分配各任务在本地、RSU和邻近车辆的最优卸载决策变量比例,其次以最小处理时延为目的在一跳通信范围内选择合适的空闲车辆作为处理部分任务的邻近车辆。仿真结果表明所提车载边缘计算中多任务部分卸载方案相较现有方案能较好地降低时延。

Nowadays,the existing vehicular applications have more stringent requirements for delay.Vehicular Edge Computing(VEC)is able to take advantage of network edges devices,such as Road Side Unit(RSU),for collaborative processing,which can effectively reduce the latency.Most existing studies assume that RSU has the sufficient computing resources to provide the unlimited services.But in fact,its computing resources will be limited with the increase of the number of processing tasks,which will restrict the delay sensitive vehicular applications.To solve this problem,a multi-task partial offloading scheme in vehicular edge computing is proposed in this paper.To minimize the total task processing delay,the remaining available computing resources of adjacent vehicles is considered under the condition of making full use of RSU computing resources in this scheme.Firstly,under the constrains of delay and resource,the optimal offloading decision variable ratio of local,RSU and adjacent vehicle for each task are allocated.Secondly,in order to minimize processing delay,the appropriate spare vehicle is selected in one-hop range as adjacent vehicles to process part of the task.Simulation results show the scheme proposed can reduce the delay better compared with other schemes.