A Performance Measurement and Analysis Method for Software-Defined Networking of IoV

被引:26
作者
Jiang, Dingde [1 ]
Wang, Zhihao [1 ]
Huo, Liuwei [1 ,2 ]
Xie, Shaowei [2 ]
机构
[1] Univ Elect Sci & Technol China, Sch Astronaut & Aeronaut, Chengdu 611731, Peoples R China
[2] Northeastern Univ, Sch Comp Sci & Engn, Shenyang 110819, Peoples R China
基金
中国国家自然科学基金;
关键词
Cloud computing; Current measurement; Extraterrestrial measurements; Switches; Computational modeling; Software measurement; Network measurement; Internet of Vehicles; packet sampling; software-defined networking; measurement points of advantage; ELECTRIC VEHICLES; CLOUD; EDGE; FRAMEWORK;
D O I
10.1109/TITS.2020.3029076
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Internet of Vehicles (IoV), which plays a significantly important role in smart future cities, has become current hot research topics. However, the high heterogeneous nature of IoV has brought many new challenges such as low network performance and difficult network management for IoV. Software-defined networking enables the efficient solution of these problem. This article studies the measurement and analysis technology for software-defined networking of IoV. A new software-defined networking-based IoV heterogeneous networking measurement framework is proposed to build software-defined networking of IoV. We propose a performance measurement and analysis method to measure and characterize its performance. The performance indexes and measure methods about the delay, loss, throughput, delay jitter is in detail derived. The switch selection mechanism is proposed to establish optimal measurement points of advantage. The packet sampling process is presented to quickly obtain the needed measurement information from massive traffic flows. To validate our measurement method and fairly characterize its measurement performance for different controllers, we conduct massive simulation experiments to systematically analyze and compare current famous controllers. In such a case, we provide more comprehensive, systematic measurement analysis for application in software-defined networking of IoV. Experiments results show that our measurement approach is feasible and effective.
引用
收藏
页码:3707 / 3719
页数:13
相关论文
共 24 条
[11]   A Joint Multi-Criteria Utility-Based Network Selection Approach for Vehicle-to-Infrastructure Networking [J].
Jiang, Dingde ;
Huo, Liuwei ;
Lv, Zhihan ;
Song, Houbing ;
Qin, Wenda .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2018, 19 (10) :3305-3319
[12]   Demand-Response Management Using a Fleet of Electric Vehicles: An Opportunistic-SDN-Based Edge-Cloud Framework for Smart Grids [J].
Kaur, Kuljeet ;
Garg, Sahil ;
Kaddoum, Georges ;
Ahmed, Syed Hassan ;
Gagnon, Francois ;
Atiquzzaman, Mohammed .
IEEE NETWORK, 2019, 33 (05) :46-53
[13]  
Keshavamurthy P., 2019, P IEEE WIR COMM NETW, P1
[14]   Service Migration in Fog Computing Enabled Cellular Networks to Support Real-Time Vehicular Communications [J].
Li, Jun ;
Shen, Xiaoman ;
Chen, Lei ;
Dung Pham Van ;
Ou, Jiannan ;
Wosinska, Lena ;
Chen, Jiajia .
IEEE ACCESS, 2019, 7 :13704-13714
[15]   Delay-Tolerant Data Traffic to Software-Defined Vehicular Networks With Mobile Edge Computing in Smart City [J].
Li, Meng ;
Si, Pengbo ;
Zhang, Yanhua .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 67 (10) :9073-9086
[16]   Resource Allocation in Vehicular Cloud Computing Systems With Heterogeneous Vehicles and Roadside Units [J].
Lin, Chun-Cheng ;
Deng, Der-Jiunn ;
Yao, Chia-Chi .
IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (05) :3692-3700
[17]   Cloud-Assisted Safety Message Dissemination in VANET-Cellular Heterogeneous Wireless Network [J].
Liu, Bingyi ;
Jia, Dongyao ;
Wang, Jianping ;
Lu, Kejie ;
Wu, Libing .
IEEE SYSTEMS JOURNAL, 2017, 11 (01) :128-139
[18]   Blockchain-Enabled Security in Electric Vehicles Cloud and Edge Computing [J].
Liu, Hong ;
Zhang, Yan ;
Yang, Tao .
IEEE NETWORK, 2018, 32 (03) :78-83
[19]   Chimera: An Energy-Efficient and Deadline-Aware Hybrid Edge Computing Framework for Vehicular Crowdsensing Applications [J].
Pu, Lingjun ;
Chen, Xu ;
Mao, Guoqiang ;
Xie, Qinyi ;
Xu, Jingdong .
IEEE INTERNET OF THINGS JOURNAL, 2019, 6 (01) :84-99
[20]   Intelligent VNFs Selection Based on Traffic Identification in Vehicular Cloud Networks [J].
Wang, Jingyu ;
He, Bo ;
Wang, Jing ;
Li, Tonghong .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (05) :4140-4147