Next Article in Journal
GPS-SLAM: An Augmentation of the ORB-SLAM Algorithm
Next Article in Special Issue
A Real-Time Automatic Plate Recognition System Based on Optical Character Recognition and Wireless Sensor Networks for ITS
Previous Article in Journal
Fano Resonance in a MIM Waveguide with Two Triangle Stubs Coupled with a Split-Ring Nanocavity for Sensing Application
Previous Article in Special Issue
Towards a Fog-Enabled Intelligent Transportation System to Reduce Traffic Jam
Open AccessArticle

Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning Networks

by 1,2,*, 1,2,*, 1,2 and 2
1
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Nan-An District, Chongqing 400065, China
2
Chongqing Key Labs of Mobile Communications, Chongqing 400065, China
*
Authors to whom correspondence should be addressed.
Sensors 2019, 19(22), 4974; https://doi.org/10.3390/s19224974
Received: 24 August 2019 / Revised: 5 November 2019 / Accepted: 12 November 2019 / Published: 15 November 2019
(This article belongs to the Special Issue Vehicular Network Communications)
Due to limited computation resources of a vehicle terminal, it is impossible to meet the demands of some applications and services, especially for computation-intensive types, which not only results in computation burden and delay, but also consumes more energy. Mobile edge computing (MEC) is an emerging architecture in which computation and storage services are extended to the edge of a network, which is an advanced technology to support multiple applications and services that requires ultra-low latency. In this paper, a task offloading approach for an MEC-assisted vehicle platooning is proposed, where the Lyapunov optimization algorithm is employed to solve the optimization problem under the condition of stability of task queues. The proposed approach dynamically adjusts the offloading decisions for all tasks according to data parameters of current task, and judge whether it is executed locally, in other platooning member or at an MEC server. The simulation results show that the proposed algorithm can effectively reduce energy consumption of task execution and greatly improve the offloading efficiency compared with the shortest queue waiting time algorithm and the full offloading to an MEC algorithm. View Full-Text
Keywords: mobile edge computing; vehicular platooning; task offloading; Lyapunov optimization mobile edge computing; vehicular platooning; task offloading; Lyapunov optimization
Show Figures

Figure 1

MDPI and ACS Style

Cui, T.; Hu, Y.; Shen, B.; Chen, Q. Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning Networks. Sensors 2019, 19, 4974. https://doi.org/10.3390/s19224974

AMA Style

Cui T, Hu Y, Shen B, Chen Q. Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning Networks. Sensors. 2019; 19(22):4974. https://doi.org/10.3390/s19224974

Chicago/Turabian Style

Cui, Taiping; Hu, Yuyu; Shen, Bin; Chen, Qianbin. 2019. "Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning Networks" Sensors 19, no. 22: 4974. https://doi.org/10.3390/s19224974

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop