Computation task offloading algorithm and system level simulation for vehicles

Qicheng ZENG; Yuxuan SUN; Sheng ZHOU

doi:10.11959/j.issn.2096-3750.2019.00120

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Computation task offloading algorithm and system level simulation for vehicles

Theory and Technology | 更新时间：2024-06-05

- Computation task offloading algorithm and system level simulation for vehicles
- Chinese Journal on Internet of Things Vol. 3, Issue 3, Pages: 62-69(2019)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-3750.2019.00120
  CLC： TN929.5
- Published：30 September 2019，
  
  Published Online：2019-09，
- 稿件说明：
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QICHENG ZENG, YUXUAN SUN, SHENG ZHOU. Computation task offloading algorithm and system level simulation for vehicles. [J]. Chinese journal on internet of things, 2019, 3(3): 62-69.
DOI：

QICHENG ZENG, YUXUAN SUN, SHENG ZHOU. Computation task offloading algorithm and system level simulation for vehicles. [J]. Chinese journal on internet of things, 2019, 3(3): 62-69. DOI： 10.11959/j.issn.2096-3750.2019.00120.

摘要

随着自动驾驶技术和车联网的发展，越来越多的车辆将具备强大的计算能力，并通过无线网络实现互联。这些计算资源不仅能够应用于自动驾驶中，也可以提供广泛的边缘计算服务。针对车辆间的计算卸载场景，以最小化平均卸载时延为目标，提出了基于在线学习的分布式计算任务卸载算法。进一步搭建了系统级仿真平台，分别在真实的高速公路和城市街区道路环境下，评估了车辆密度、任务卸载份数对平均卸载时延的影响，为不同交通环境下的服务资源分配部署提供了参考。

Abstract

With the development of autonomous driving and vehicular network

more and more vehicles will have powerful computing capabilities and connection with each other via wireless network.These computing resources can not only be applied to automatic driving

but also provide a wide range of edge computing services.Aiming at the task offloading among vehicles

a distributed task offloading algorithm based on online learning was proposed to minimize the average offloading delay.Furthermore

a system-level simulation platform was built to evaluate the impact of vehicle density and number of tasks on the average offloading delay in both highway and urban scenarios.The results provide a reference for the resource allocation and deployment of task offloading in different traffic situations.

关键词

车联网Veins计算任务卸载系统级仿真

Keywords

Internet of vehiclesVeinscomputation task offloadingsystem level simulation

references

LEE E, LEE E K, GERLA M ,et al. Vehicular cloud networking:architecture and design principles[J]. IEEE Communications Magazine, 2014,52(2): 148-155.

HU Y C, PATEL M, SABELLA D ,et al. Mobile edge computing—a key technology towards 5G[J]. ETSI White Paper, 2015,11(11): 1-16.

SHIH Y Y, CHUNG W H, PANG A C ,et al. Enabling low-latency applications in fog-radio access networks[J]. IEEE Network, 2016,31(1): 52-58.

HOU X S, LI Y, CHEN M ,et al. Vehicular fog computing:a viewpoint of vehicles as the infrastructures[J]. IEEE Transactions on Vehicular Technology, 2016,65(6): 3860-3873.

ABDELHAMID S, HASSANEIN H S, TAKAHARA G . Vehicle as a resource (VaaR)[J]. IEEE Network, 2015,29(1): 12-17.

BITAM S, MELLOUK A, ZEADALLY S . VANET-cloud:a generic cloud computing model for vehicular Ad Hoc networks[J]. IEEE Wireless Communications, 2015,22(1): 96-102.

JANG I, CHOO S J, KIM M ,et al. The software-defined vehicular cloud:a new level of sharing the road[J]. IEEE Vehicular Technology Magazine, 2017,12(2): 78-88.

ZHOU S, SUN Y X, JIANG Z Y ,et al. Exploiting moving intelligence:delay-optimized computation offloading in vehicular fog networks[J]. IEEE Communications Magazine, 2019,57(5): 49-55.

SUN Y, GUO X Y, SONG J H ,et al. Adaptive learning-based task offloading for vehicular edge computing systems[J]. IEEE Transactions on Vehicular Technology, 2019,68(4): 3061-3074.

SUN Y X, SONG J H, ZHOU S ,et al. Task replication for vehicular edge computing:a combinatorial multi-armed bandit based approach[C]// 2018 IEEE Global Communications Conference (GLOBECOM). IEEE, 2018: 1-7.

ZHENG K, MENG H L, CHATZIMISIOS P ,et al. An SMDP-based resource allocation in vehicular cloud computing systems[J]. IEEE Transactions on Industrial Electronics, 2015,62(12): 7920-7928.

FENG J Y, LIU Z, WU C L ,et al. AVE:autonomous vehicular edge computing framework with ACO-based scheduling[J]. IEEE Transactions on Vehicular Technology, 2017,66(12): 10660-10675.

DORIGO M, GAMBARDELLA L M . Ant colony system:a cooperative learning approach to the traveling salesman problem[J]. IEEE Transactions on Evolutionary Computation, 1997,1(1): 53-66.

JIANG Z Y, ZHOU S, GUO X Y ,et al. Task replication for deadline-constrained vehicular cloud computing:optimal policy,performance analysis,and implications on road traffic[J]. IEEE Internet of Things Journal, 2017,5(1): 93-107.

GRUNDMANN M, KWATRA V, HAN M ,et al. Efficient hierarchical graph-based video segmentation[C]// 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE, 2010: 2141-2148.

CHEN W, WANG Y J, YUAN Y . Combinatorial multi-armed bandit:general framework and applications[C]// International Conference on Machine Learning, 2013(28): 151-159.

CODECA L, FRANK R, ENGEL T . Luxembourg SUMO traffic (lust) scenario:24 hours of mobility for vehicular networking research[C]// 2015 IEEE Vehicular Networking Conference (VNC). IEEE, 2015: 1-8.

KRAU S . Microscopic modeling of traffic flow:investigation of collision free vehicle dynamics[D]. Centre for Aerospace and Space, 1998.

SOMMER C, DRESSLER F . Using the right two-ray model? a measurement based evaluation of PHY models in VANETs[C]// Proceedings of 17th ACM International Conference on Mobile Computing and Networking (MobiCom 2011). ACM, 2011: 1-3.

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