Analytical offloading design for mobile edge computing-based smart internet of vehicle

EURASIP Journal on Advances in Signal Processing

卷:2022

Chengyuan Fan¹  Jiangtao Ou¹  Fusheng Zhu²  Maobin Tang³  Junjuan Xia³  Jinrong Lu³  Lunyuan Chen³ 

[1] AI Sensing Technology;

[2] Guangdong New Generation Communication and Network Innovative Institute (GDCNi);

[3] School of Computer Science, Guangzhou University;

关键词: Internet of vehicle;    Mobile edge computing;    Offloading strategy;    Latency;    Energy consumption;   

DOI  :  10.1186/s13634-022-00867-2

来源: DOAJ

【 摘 要 】

Abstract In this paper, we investigate how to analytically design an analytical offloading strategy for a multiuser mobile edge computing (MEC)-based smart internet of vehicle (IoV), where there are multiple computational access points (CAPs) which can help compute tasks from the vehicular users. As it is difficult to derive an analytical offloading ratio for a general MEC-based IoV network, we turn to provide an analytical offloading scheme for some special MEC networks including one-to-one, one-to-two and two-to-one cases. For each case, we study the system performance by using the linear combination of latency and energy consumption, and derive the analytical offloading ratio through minimizing the system cost. Simulation results are finally presented to verify the proposed studies. In particular, the proposed analytical offloading scheme can achieve the optimal performance of the brute force (BF) scheme. The analytical results in this paper can serve as an important reference for the analytical offloading design for a general MEC-based IoV.

【 授权许可】

Unknown