基于势博弈的车载边缘计算信道分配方法

doi:10.12263/DZXB.20200994

电子学报 ›› 2021, Vol. 49 ›› Issue (5): 851-860.DOI: 10.12263/DZXB.20200994

所属专题：面向自动驾驶和智慧交通协同的通信与控制

• 面向自动驾驶和智慧交通协同的通信与控制 • 上一篇下一篇

基于势博弈的车载边缘计算信道分配方法

许新操¹, 刘凯¹, 刘春晖¹, 蒋豪¹, 郭松涛¹, 吴巍炜²

1. 重庆大学计算机学院, 重庆 400044;
2. 东南大学计算机科学与工程学院, 江苏南京 210000

收稿日期:2020-09-07 修回日期:2020-12-02 出版日期:2021-05-25
- 通讯作者:
- 刘凯(通信作者) 男,1984年8月出生,四川成都人.重庆大学计算机学院教授、博士生导师.2011年获得香港城市大学博士学位,2011年11月至2014年5月作为博士后先后工作于新加坡南洋理工大学、香港城市大学、香港浸会大学.主要研究方向包括车联网、边缘计算、普适计算、智能计算等. E-mail:liukai0807@cqu.edu.cn
- 作者简介:
- 许新操 男,1994年11月出生,江西赣州人.2017年获得中北大学工学学士学位.目前在重庆大学计算机学院攻读博士学位,主要研究方向包括车联网、边缘计算、博弈论等. E-mail:near@cqu.edu.cn;刘春晖 男,1997年3月出生,重庆合川人.2019年获得重庆大学工学学士学位.目前在重庆大学计算机学院攻读硕士学位.主要研究方向包括车联网、端边云协同、边缘智能等. E-mail:chhliu0302@cqu.edu.cn;蒋豪男,1998年1月出生,湖南常德人.2020年获得重庆大学工学学士学位.目前在重庆大学计算机学院攻读硕士学位.主要研究方向包括车联网、边缘计算等. E-mail:artanis@cqu.edu.cn;郭松涛 男,1975年12月出生,河南西平人.重庆大学计算机学院教授、博士生导师.主要研究方向包括智能边缘计算、移动自组织网络、物联网等. E-mail:guosongtao@cqu.edu.cn;吴巍炜 男,1983年11月出生,福建人.东南大学计算机科学与工程学院教授、博士生导师.2006年获得华南理工大学学士学位,2011年分别获得香港城市大学与中国科技大学博士学位.主要研究方向包括群智计算、物联网与大数据、博弈论、强化学习、调度算法等. E-mail:weiweiwu@seu.edu.cn
- 基金资助:
- 国家重点研发计划 (No.2017YFB1003000）; 国家自然科学基金 (No.61872049，No.61672154，No.61972086）

Potential Game Based Channel Allocation for Vehicular Edge Computing

XU Xin-cao¹, LIU Kai¹, LIU Chun-hui¹, JIANG Hao¹, GUO Song-tao¹, WU Wei-wei²

1. College of Computer Science, Chongqing University, Chongqing 400044, China;
2. School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu 210000, China

Received:2020-09-07 Revised:2020-12-02 Online:2021-05-25 Published:2021-05-25

摘要/Abstract

摘要： 针对车载边缘计算环境中,边缘节点在为不同数据传输任务分配信道时产生的同信道干扰(Co-Channel Interferences,CCI)问题,本文形式化定义了车载边缘计算信道分配问题,致力于为不同数据传输任务合理分配信道,最大化数据传输任务的完成率.利用势博弈模型将全局优化的信道分配问题转化为边缘节点间的分布式信道分配博弈,并证明了信道分配博弈中纳什均衡的存在性.提出了基于激励的概率更新策略选择(Incentive-based Probability Update and Strategy Selection)算法,根据迭代中所选策略的激励值更新策略选择概率,并分析算法结果收敛至纳什均衡.最后,通过仿真实验验证了本文算法的收敛性以及收敛结果纳什均衡的有效性,且在任务完成率及信道利用效率上优于现有代表性算法.

关键词: 车载边缘计算, 信道分配, 势博弈, 分布式调度

Abstract: In vehicular edge computing environments,the Co-channel interferences (CCI)is a critical problem when edge nodes allocate channels for different data transmission tasks.This article formulates the problem of channel allocation in vehicular edge computing,aiming at allocating sub-channels for different data transmission tasks and maximizing the ratio of successful data transmission.We transform the global optimization problem of channel allocation into a channel allocation potential game,and prove the existence of nash equilibrium.We propose an Incentive-based probability update and strategy selection algorithm,which updates the strategy selection probability according to the incentive value of the selected strategy in each iteration,and further analyzes the Nash equilibrium converge of the algorithm.Finally,we verify the convergence of the proposed algorithm and the effectiveness of the Nash equilibrium.The experimental results show that the proposed algorithm outperforms existing representative algorithms in terms of the ratio of successful data transmission and channel utilization efficiency.

Key words: vehicular edge computing, channel allocation, potential game, distributed scheduling

中图分类号:

TN919

许新操, 刘凯, 刘春晖, 蒋豪, 郭松涛, 吴巍炜. 基于势博弈的车载边缘计算信道分配方法[J]. 电子学报, 2021, 49(5): 851-860.

XU Xin-cao, LIU Kai, LIU Chun-hui, JIANG Hao, GUO Song-tao, WU Wei-wei. Potential Game Based Channel Allocation for Vehicular Edge Computing[J]. Acta Electronica Sinica, 2021, 49(5): 851-860.

参考文献

[1] Shi W S,Cao J,Zhang Q,et al.Edge computing:Vision and challenges[J].IEEE Internet of Things Journal,2016,3(5):637-646.
[2] Dai Y Y,Xu D,Zhang K,et al.Deep reinforcement learning and permissioned blockchain for content caching in vehicular edge computing and networks[J].IEEE Transactions on Vehicular Technology,2020,69(4):4312-4324.
[3] Guo H Z,Liu J J,Ren J,et al.Intelligent task offloading in vehicular edge computing networks[J].IEEE Wireless Communications,2020,27(4):126-132.
[4] 张彦,张科,曹佳钰.边缘智能驱动的车联网[J].物联网学报,2018,2(4):40-48. Zhang Y,Zhang K,Cao J Y.Internet of vehicles empowered by edge intelligence[J].Chinese Journal on Internet of Things,2018,2(4):40-48.(in Chinese).
[5] Liu K,Ng J K Y,Lee V C S,et al.Cooperative data scheduling in hybrid vehicular ad hoc networks:VANET as a software defined network[J].IEEE/ACM Transactions on Networking,2016,24(3):1759-1773.
[6] 彭鑫,李仁发,付彬,等.基于路径时延模型的车联网数据分发方案[J].电子学报,2017,45(9):2195-2201. Peng X,Li R F,Fu B,et al.Data dissemination based on road delay for VANETs[J].Acta Electronica Sinica,2017,45(9):2195-2201.(in Chinese).
[7] Liu C H,Liu K,Guo S T,et al.Adaptive offloading for time-critical tasks in heterogeneous Internet of vehicles[J].IEEE Internet of Things Journal,2020,7(9):7999-8011.
[8] Kadhim A J,Seno S A H.Energy-efficient multicastrouting protocol based on SDN and fog computing for vehicular networks[J].Ad Hoc Networks,2019,84:68-81.
[9] 张德干,崔玉亚,陈晨,等.一种面向高速路车联网场景的自适应路由方法[J].电子学报,2020,48(1):172-179. Zhang D G,Cui Y Y,Chen C,et al.An adaptive routing method for high-speed-road scenario of the Internet of vehicle[J].Acta Electronica Sinica,2020,48(1):172-179.(in Chinese).
[10] Ning Z L,Wang X J,Huang J.Mobile edge computing-enabled 5G vehicular networks:Toward the integration of communication and computing[J].IEEE Vehicular Technology Magazine,2019,14(1):54-61.
[11] Xiao K,Liu K,Xu X C,et al.Efficient fog-assisted heterogeneous data services in software defined VANETs[J].Journal of Ambient Intelligence and Humanized Computing,2021,12:261-273.
[12] Zhang K,Leng S P,Peng X,et al.Artificial intelligence inspired transmission scheduling in cognitive vehicular communications and networks[J].IEEE Internet of Things Journal,2019,6(2):1987-1997.
[13] Eshteiwi K,Kaddoum G,Selim B,et al.Impact of Co-channel interference and vehicles as obstacles on full-duplex V2V cooperative wireless network[J].IEEE Transactions on Vehicular Technology,2020,69(7):7503-7517.
[14] Patra M,Thakur R,Murthy C S R.Improving delay and energy efficiency of vehicular networks using mobile femto access points[J].IEEE Transactions on Vehicular Technology,2017,66(2):1496-1505.
[15] Lee K,Lee J R,Choi H H.Learning-based joint optimization of transmit power and harvesting time in wireless-powered networks with Co-channel interference[J].IEEE Transactions on Vehicular Technology,2020,69(3):3500-3504.
[16] Liu K,Xu X C,Chen M L,et al.A hierarchical architecture for the future Internet of vehicles[J].IEEE Communications Magazine,2019,57(7):41-47.
[17] Sadek A K,Han Z,Liu K J R.Distributed relay-assignment protocols for coverage expansion in cooperative wireless networks[J].IEEE Transactions on Mobile Computing,2010,9(4):505-515.
[18] Wyner A.Recent results in the Shannon theory[J].IEEE Transactions on Information Theory,1974,20(1):2-10.
[19] Sun Z M,Liu Y H,Wang J,et al.Non-cooperative game of throughput and hash length for adaptive merkle tree in mobile wireless networks[J].IEEE Transactions on Vehicular Technology,2019,68(5):4625-4650.
[20] Zhang T T,Qin C,Molisch A F,et al.Joint allocation of spectral and power resources for non-cooperative wireless localization networks[J].IEEE Transactions on Communications,2016,64(9):3733-3745.
[21] 张婷,张德干,赵彭真,等.基于博弈策略的能效优化的子载波分配方法[J].电子学报,2019,47(12):2561-2568. Zhang T,Zhang D G,Zhao P Z,et al.A kind of novel sub-carrier dispatching approach based on game strategy for EEO[J].Acta Electronica Sinica,2019,47(12):2561-2568.(in Chinese).
[22] Yamamoto K.A comprehensive survey of potential game approaches to wireless networks[J].IEICE Transactions on Communications,2015,E98.B(9):1804-1823.
[23] Wang J H,Liu K,Li B,et al.Delay-sensitive multi-period computation offloading with reliability guarantees in fog networks[J].IEEE Transactions on Mobile Computing,2020,19(9):2062-2075.
[24] Yu W,Rhee W,Boyd S,et al.Iterative water-filling for gaussian vector multiple-access channels[J].IEEE Transactions on Information Theory,2004,50(1):145-152.

基于势博弈的车载边缘计算信道分配方法

Potential Game Based Channel Allocation for Vehicular Edge Computing

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	刘雷, 陈晨, 冯杰, 肖婷婷, 裴庆祺. 车载边缘计算卸载技术研究综述[J]. 电子学报, 2021, 49(5): 861-871.
[2]	汪志勇, 张沪寅, 徐宁, 郝圣. 认知无线电网络中基于随机学习博弈的信道分配与功率控制[J]. 电子学报, 2018, 46(12): 2870-2877.
[3]	乔宏, 张大方, 谢鲲, 何施茗, 张继. 多射频无线mesh网中的联合协作路由与信道分配算法[J]. 电子学报, 2016, 44(6): 1400-1405.
[4]	胡洁, 赵祚喜, 陈润恩. 分布式网络中基于一致性的信道分配算法[J]. 电子学报, 2014, 42(6): 1132-1138.
[5]	管明祥, 郭庆, 顾学迈. 一种基于距离判决的HAPS通信无线DCA算法[J]. 电子学报, 2013, 41(1): 18-23.
[6]	贾杰, 李燕燕, 陈剑, 王兴伟. 认知无线网状网中基于差分演化的功率控制与信道分配[J]. 电子学报, 2013, 41(1): 62-67.
[7]	杜振国;洪佩琳;周武旸;薛开平. 多射频无线Mesh网中的接口分域信道分配[J]. 电子学报, 2011, 39(3): 723-726.
[8]	王晶;管雪涛;杨春;张杨;程旭. CBLA:多信道无线网状网络负载感知的分簇式信道分配[J]. 电子学报, 2010, 38(3): 546-551.
[9]	纪守领;李金宝;郭龙江;张德升;惠丽. Multi-Radio传感器网络信道分配算法的研究[J]. 电子学报, 2010, 38(2A): 117-122.
[10]	束永安;洪佩琳;覃振权. 无线网状网中基于干扰模型的多信道分配策略[J]. 电子学报, 2008, 36(7): 1256-1260.
[11]	党安红;张敏;朱世华;汤俊雄. 一种新的优化动态信道分配策略及建模分析[J]. 电子学报, 2004, 32(7): 1152-1155.
[12]	党安红;汤俊雄;朱世华. 蜂窝移动通信系统中的一种新的优化信道分配模型[J]. 电子学报, 2003, 31(7): 1002-1004.
[13]	邬海涛, 林宇, 孙亮, 程时端. WLFVC:WLAN中的分布式公平调度机制[J]. 电子学报, 2002, 30(S1): 2071-2074.
[14]	钱学荣;岳殿武;张力军. 频率选择性衰落信道中多用户OFDM系统的自适应分配算法[J]. 电子学报, 2002, 30(4): 508-511.
[15]	李建军;樊平毅;曹志刚. 一种基于灌水原理的多载波CDMA系统子信道分配方案[J]. 电子学报, 2001, 29(10): 1301-1305.