基于负载均衡的VEC服务器联合计算任务卸载方案

在车载边缘计算(Vehicular Edge Computing,VEC)网络中,车辆计算资源受限导致无法处理海量的计算任务,需要将车载应用产生的计算任务卸载到VEC服务器上进行处理。但车辆的移动性和区域部署的差异性易导致VEC服务器负载不均衡,造成了计算卸载效率和资源利用率降低。为解决该问题,提出一种计算卸载和资源分配方案,以使用户效用最大化。将用户效用最大化问题转化成服务器选择决策和卸载比例与计算资源分配联合优化两个子问题,在此基础上设计基于匹配的服务器选择决策算法和基于Adam梯度优化法的计算任务卸载比例与资源分配联合优化算法,并对上述两种算法进行联合迭代,直至收敛,从而得到近似最优解以达到负载均衡。仿真结果表明,相比最近卸载方案和预测卸载方案,该方案能有效降低计算任务处理时延和车辆能耗,增大车辆效用,促进负载均衡。

Computational Task Offloading Scheme Based on Load Balance for Cooperative VEC Servers

In the Vehicular Edge Computing(VEC)network,a large number of computational tasks cannot be processed due to the vehicle’s limited computation resource.Therefore,computational tasks generated by on-board applications need to be offloa-ded to the VEC servers for processing.However,the mobility of vehicles and the differences in regional deployment lead to the unbalance among VEC servers,resulting in low computation offloading efficiency and resource utilization.In order to solve the problem,a scheme of computation offloading and resource utilization is proposed to maximize the utility of users.The problem of user utility maximization is decoupled into two subproblems,the VEC server selection decision algorithm based on matching and the joint optimization algorithm for offloading ratio and computation resource allocation based on Adam are proposed to solve the subproblems respectively.After that,the above two algorithms are iterated together until convergence,and the approximate optimal solution is obtained to achieve the load balance.The simulation results show that the proposed scheme can effectively decrease the processing delay of computational tasks,save vehicle’s energy,enhance the vehicle utility,and perform well on load balance compared to the nearest offloading scheme and the predictive offloading scheme.