车联网中自适应联合计算卸载资源分配算法

Resource allocation algorithm for adaptive joint computing offloading in C-V2X

为降低车联网(C-V2X)中计算任务的时延与能耗,提出一种自适应的联合计算卸载资源分配算法。考虑多因素,多平台(本地计算、云计算、移动边缘计算(MEC)、空闲车辆计算)卸载,将计算卸载决策和资源分配建模为多约束优化问题。在粒子群算法基础上,提出粒子矩阵编码方式,联合优化车辆卸载决策、各平台任务卸载比例、MEC资源分配。提出粒子修正算法,结合罚函数法,解决多约束优化问题。仿真结果表明,与其它算法相比,该算法能在满足最大容忍时延的同时,最小化系统总成本。

To reduce the delay and energy consumption of computing tasks in the cellular vehicles to everything(C-V2X),an adaptive joint computing offload resource allocation algorithm was proposed.Considering multiple factors,multi-platform(local computing,cloud computing,mobile edge computing(MEC),idle vehicle computing)offloading,computing offloading decision and resource allocation were modelled as the multi-constrained optimization problem.Based on the particle swarm optimization algorithm,a particle matrix coding method was proposed to jointly optimize vehicle offloading decision,task offloading ratio of each platform,and MEC resource allocation.Particle correction algorithm was proposed to solve multi-constrained optimization problem,and penalty function method was combined.Simulation results indicate that compared with other algorithms,this algorithm can meet the maximum tolerance delay while minimizing the total cost of systematization.