TRAFFIC OFFLOADING METHOD FOR V2X/5G NETWORKS BASED ON THE EDGE COMPUTING SYSTEM

Author(s):  
А.Г. ВЛАДЫКО ◽  
А.С. МУТХАННА ◽  
А.Е. КУЧЕРЯВЫЙ

Разработана структура системы V2X(Vehicle-to-Everything), позволяющей на базе сети 5G организовать взаимодействие между объектами дорожной инфраструктуры, беспилотными и высокоавтоматизированными транспортными средствами, пешеходами и другими сетями. Для производительной работы в условиях плотного трафика транспортных средств в системе V2X использованы технология мобильных граничных вычислений MEC (Mobile Edge Computing) и алгоритм выгрузки трафика, позволяющий управлять нагрузкой данных на граничные и облачные серверы. Результаты моделирования для различных сценариев показали, что предложенные структура и алгоритм выгрузки могут значительно снизить задержки в передаче данных и энергопотребление системы. The V2X (Vehicle-to-Everything) system structure has been developed, which allows, based on 5G network, to organize interaction between road infrastructure objects, unmanned and highly automated vehicles, pedestrians, and other networks. For efficient operation in conditions of dense vehicle traffic, the V2X system uses the mobile edge computing technology and a traffic offloading algorithm, which allows managing the data load on the edge cloud servers. Simulation results for various scenarios showed that the proposed structure and offloading algorithm can significantly reduce data transfer delays and system power consumption.

2021 ◽  
Vol 561 ◽  
pp. 70-80
Author(s):  
Guangshun Li ◽  
Xinrong Ren ◽  
Junhua Wu ◽  
Wanting Ji ◽  
Haili Yu ◽  
...  

Author(s):  
Liang Lyu ◽  
Fanzi Zeng ◽  
Zhu Xiao ◽  
Chengyuan Zhang ◽  
Hongbo Jiang ◽  
...  

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3231 ◽  
Author(s):  
Jiuyun Xu ◽  
Zhuangyuan Hao ◽  
Xiaoting Sun

Mobile edge computing (MEC) has become more popular both in academia and industry. Currently, with the help of edge servers and cloud servers, it is one of the substantial technologies to overcome the latency between cloud server and wireless device, computation capability and storage shortage of wireless devices. In mobile edge computing, wireless devices take responsibility with input data. At the same time, edge servers and cloud servers take charge of computation and storage. However, until now, how to balance the power consumption of edge devices and time delay has not been well addressed in mobile edge computing. In this paper, we focus on strategies of the task offloading decision and the influence analysis of offloading decisions on different environments. Firstly, we propose a system model considering both energy consumption and time delay and formulate it into an optimization problem. Then, we employ two algorithms—Enumerating and Branch-and-Bound—to get the optimal or near-optimal decision for minimizing the system cost including the time delay and energy consumption. Furthermore, we compare the performance between two algorithms and draw the conclusion that the comprehensive performance of Branch-and-Bound algorithm is better than that of the other. Finally, we analyse the influence factors of optimal offloading decisions and the minimum cost in detail by changing key parameters.


2020 ◽  
Vol 17 (8) ◽  
pp. 45-57
Author(s):  
Xiequn Dong ◽  
Xuehua Li ◽  
Xinwei Yue ◽  
Wei Xiang

Sign in / Sign up

Export Citation Format

Share Document