论文摘要
With the emergence of advanced vehicular applications, the challenge of satisfying computational and communication demands of vehicles has become increasingly prominent. Fog computing is a potential solution to improve advanced vehicular services by enabling computational offloading at the edge of network. In this paper, we propose a fog-cloud computational offloading algorithm in Internet of Vehicles（IoV） to both minimize the power consumption of vehicles and that of the computational facilities. First, we establish the system model, and then formulate the offloading problem as an optimization problem, which is NP-hard. After that, we propose a heuristic algorithm to solve the offloading problem gradually. Specifically, we design a predictive combination transmission mode for vehicles, and establish a deep learning model for computational facilities to obtain the optimal workload allocation. Simulation results demonstrate the superiority of our algorithm in energy efficiency and network latency.
论文目录
文章来源
类型: 期刊论文
作者: Xiaojie Wang,Xiang Wei,Lei Wang
来源: 中国通信 2019年03期
年度: 2019
分类: 信息科技,经济与管理科学,工程科技Ⅱ辑
专业: 汽车工业,自动化技术
单位: School of Software, Dalian University of Technology,School of Computer Science and Engineering, Beihang University
基金: supported by National Natural Science Foundation of China with No. 61733002 and 61842601,National Key Research and Development Plan 2017YFC0821003-2,the Fundamental Research Funds for the Central University with No. DUT17LAB16 and No. DUT2017TB02
分类号: TP18;U463.6
页码: 81-91
总页数: 11
文件大小: 1066K
下载量: 75