计算机科学
移动边缘计算
拉格朗日乘数
方案(数学)
能源消耗
任务(项目管理)
GSM演进的增强数据速率
边缘计算
迭代法
实时计算
数学优化
算法
人工智能
工程类
数学
数学分析
系统工程
电气工程
作者
Jing Tang,Xujie Li,Mengran Jin,Yong Lü
标识
DOI:10.1109/wcsp52459.2021.9613232
摘要
The mobility of the vehicle poses new challenges to the unloading decision. In view of this situation, this paper proposes a unloading scheme of vehicle edge computing (VEC) based on mobile sensing, so that vehicles with computing ability can provide VEC services in the vehicle fog network, so as to solve the problem of high-speed mobility of vehicles. Firstly, we divide the running time of each vehicle into several same time slots. In each time slot, we believe that the distance between the vehicle and the base station is constant. RSU distributes a task to multiple vehicles according to the ratio, and optimizes the energy consumption of the system by optimizing the task unloading ratio. Then a Lagrange and its dual method based on convex algorithm is used to solve this problem, and a low complexity algorithm is proposed to optimize the task unloading ratio, and the Lagrange multiplier is iterative until it converges. Finally, the simulation results verify the efficient performance of the proposed scheme. Compared with other algorithms, the proposed algorithm not only improves the utilization rate of vehicle computing resources, but also minimizes the overall energy consumption of the system.
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