Research on adaptive dual task offloading decision algorithm for parking space recommendation service

作     者：Peng Weiping Su Zhe Song Cheng Jia Zongpu 

作者机构：School of Computer Science and TechnologyHenan Polytechnic UniversityJiaozuo 454000China 

出 版 物：《The Journal of China Universities of Posts and Telecommunications》 (中国邮电高校学报（英文版）)

年 卷 期：2019年第26卷第6期

页      面：30-42页

核心收录：

学科分类：0810[工学-信息与通信工程] 1205[管理学-图书情报与档案管理] 0839[工学-网络空间安全] 081203[工学-计算机应用技术] 08[工学] 0838[工学-公安技术] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Scientific Research Project of Henan Province(182102110333) the Doctoral Support Research Project of Henan Polytechnic University(B2012050) the Funding Project for the Young Backbone Teachers of Higher Education Institutions in Henan Province(2019GGJS061) 

主　　题：parking space recommendation service Internet of vehicles RSU adaptive dual task offloading 

摘      要：In order to improve the efficiency of tasks processing and reduce the energy consumption of new energy vehicle(NEV), an adaptive dual task offloading decision-making scheme for Internet of vehicles is proposed based on information-assisted service of road side units(RSUs) and task offloading theory. Taking the roadside parking space recommendation service as the specific application Scenario, the task offloading model is built and a hierarchical self-organizing network model is constructed, which utilizes the computing power sharing among nodes, RSUs and mobile edge computing(MEC) servers. The task scheduling is performed through the adaptive task offloading decision algorithm, which helps to realize the available parking space recommendation service which is energy-saving and environmental-friendly. Compared with these traditional task offloading decisions, the proposed scheme takes less time and less energy in the whole process of tasks. Simulation results testified the effectiveness of the proposed scheme.