车载多接入边缘网络中联合资源分配和动态任务卸载方案

针对车联网中车辆移动速度过快产生的任务卸载失败问题,设计了一个有效的任务卸载风险评估模型,并提出了联合资源分配的动态任务卸载方案。将时间、能耗和风险共同建模为系统效用,通过联合优化卸载决策、资源分配来最大化系统效用。优化问题被公式化为混合整数非线性规划,在给定卸载决策的情况下,利用凸优化技术解决计算资源分配问题,功率分配通过分式规划技术来优化。仿真分析了车辆移动性对系统效用的影响,证明了所提方案的合理性。

Joint resource allocation and dynamic task offloading scheme in vehicle multi-access edge network

Aiming at the problem of task offloading failure caused by the excessively fast vehicle moving in the Internet of vehicles, an effective task offloading risk assessment model was designed, and a dynamic task offloading scheme based on joint resource allocation was proposed. Time, energy consumption, and risk were jointly modeled as system utility, and the system utility was maximized through joint optimization of offloading decision and resource allocation. The optimization problem was formulated as a mixed integer nonlinear programming. Convex optimization techniques were used to solve the computational resource allocation problem under a given offloading decision, power allocation was optimized through fractional programming technology. The simulation analyzes the impact of vehicle mobility on system utility, and the rationality of the proposed scheme is proved.