A Task Offloading Scheme in Vehicular Fog and Cloud Computing System

IEEE Access

Qiang Fan¹  Ziyang Wang²  Qiong Wu³  Hongmei Ge³  Zhengquan Li³  Hanxu Liu³ 

[1] Department of Electrical and Computer Engineering, Advanced Networking Laboratory, New Jersey Institute of Technology, Newark, NJ, USA;Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China;Key Laboratory of Advanced Process Control for Light Industry, School of Internet of Things Engineering, Jiangnan University, Wuxi, China;

关键词: Vehicular fog computing;    cloud computing;    task offloading;    semi-Markov decision process;   

DOI  :  10.1109/ACCESS.2019.2961802

来源: DOAJ

【 摘 要 】

Vehicular fog and cloud computing (VFCC) system, which provides huge computing power for processing numerous computation-intensive and delay sensitive tasks, is envisioned as an enabler for intelligent connected vehicles (ICVs). Although previous works have studied the optimal offloading scheme in the VFCC system, no existing work has considered the departure of vehicles that are processing tasks, i.e., the occupied vehicles. However, vehicles leaving the system with uncompleted tasks will affect the overall performance of the system. To solve the problem, in this paper, we study the optimal offloading scheme that considers the departure of occupied vehicles. We first formulate the task offloading problem as an semi-Markov decision process (SMDP). Then we design the value iteration algorithm for the SMDP to maximize the total long-term reward of the VFCC system. Finally, the numerical results demenstrate that the proposed offloading scheme can achieve higher system reward than the greedy scheme.

【 授权许可】

Unknown