Software Defined Networking-based Vehicular Adhoc Network with Fog Computing

被引:0
|
作者
Truong, Nguyen B. [1 ]
Lee, Gyu Myoung [2 ]
Ghamri-Doudane, Yacine [3 ]
机构
[1] Dasan Networks Corp, Songnam 463400, Gyeonggi Do, South Korea
[2] Liverpool John Moores Univ, Sch Comp & Math Sci, Liverpool L3 3AF, Merseyside, England
[3] Univ La Rochelle, Sci & Technol Pole, Lab L3i, F-17042 La Rochelle 1, France
关键词
Software Defined Network; SDN; Fog Computing; Edge Computing; VANET; OpenFlow; Road-side-unit; RSU; Road-side-unit Controller; RSUC; Base Station; Lane Change; Data Streaming;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Vehicular Adhoc Networks (VANETs) have been attracted a lot of research recent years. Although VANETs are deployed in reality offering several services, the current architecture has been facing many difficulties in deployment and management because of poor connectivity, less scalability, less flexibility and less intelligence. We propose a new VANET architecture called FSDN which combines two emergent computing and network paradigm Software Defined Networking (SDN) and Fog Computing as a prospective solution. SDN-based architecture provides flexibility, scalability, programmability and global knowledge while Fog Computing offers delay-sensitive and location-awareness services which could be satisfy the demands of future VANETs scenarios. We figure out all the SDN-based VANET components as well as their functionality in the system. We also consider the system basic operations in which Fog Computing are leveraged to support surveillance services by taking into account resource manager and Fog orchestration models. The proposed architecture could resolve the main challenges in VANETs by augmenting Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Base Station communications and SDN centralized control while optimizing resources utility and reducing latency by integrating Fog Computing. Two use-cases for non-safety service (data streaming) and safety service (Lane-change assistance) are also presented to illustrate the benefits of our proposed architecture.
引用
收藏
页码:1202 / 1207
页数:6
相关论文
共 50 条
  • [31] Named Data Networking for Software Defined Vehicular Networks
    Ahmed, Syed Hassan
    Bouk, Safdar Hussain
    Kim, Dongkyun
    Rawat, Danda B.
    Song, Houbing
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2017, 55 (08) : 60 - 66
  • [32] Software-Defined Vehicular Networking: Opportunities and Challenges
    Cardona, Nelson
    Coronado, Estefania
    Latre, Steven
    Riggio, Roberto
    Marquez-Barja, Johann M.
    [J]. IEEE ACCESS, 2020, 8 : 219971 - 219995
  • [33] Software-defined networking in vehicular networks: A survey
    Mekki, Tesnim
    Jabri, Issam
    Rachedi, Abderrezak
    Chaari, Lamia
    [J]. TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES, 2022, 33 (10)
  • [34] Secure and Reliable IoT Networks Using Fog Computing with Software-Defined Networking and Blockchain
    Muthanna, Ammar
    Ateya, Abdelhamied A.
    Khakimov, Abdukodir
    Gudkova, Irina
    Abuarqoub, Abdelrahman
    Samouylov, Konstantin
    Koucheryavy, Andrey
    [J]. JOURNAL OF SENSOR AND ACTUATOR NETWORKS, 2019, 8 (01)
  • [35] A mobile edge computing/software-defined networking-enabled architecture for vehicular networks
    Muthanna, Ammar
    Shamilova, Regina
    Ateya, Abdelhamied A.
    Paramonov, Alexander
    Hammoudeh, Mohammad
    [J]. INTERNET TECHNOLOGY LETTERS, 2020, 3 (06)
  • [36] QoS Aware and Fault Tolerance Based Software-Defined Vehicular Networks Using Cloud-Fog Computing
    Syed, Sidra Abid
    Rashid, Munaf
    Hussain, Samreen
    Azim, Fahad
    Zahid, Hira
    Umer, Asif
    Waheed, Abdul
    Zareei, Mahdi
    Vargas-Rosales, Cesar
    [J]. SENSORS, 2022, 22 (01)
  • [37] Distributed software defined network-based fog to fog collaboration scheme
    Kabeer, Muhammad
    Yusuf, Ibrahim
    Sufi, Nasir Ahmad
    [J]. PARALLEL COMPUTING, 2023, 117
  • [38] Flow Path Computing in Software Defined Networking
    Mon, Ohmmar Min
    Mon, Myat Thida
    [J]. 2019 INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION TECHNOLOGIES (ICAIT), 2019, : 13 - 18
  • [39] Residual based temporal attention convolutional neural network for detection of distributed denial of service attacks in software defined network integrated vehicular adhoc network
    Karthik, V.
    Lakshmi, R.
    Abraham, Salini
    Ramkumar, M.
    [J]. INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT, 2024, 34 (03)
  • [40] An effective Vehicular Adhoc Network Using Cloud Computing: A Review
    Netra, K.
    Manjunath, K. G.
    Shankar, Achyut
    [J]. 2019 9TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, DATA SCIENCE & ENGINEERING (CONFLUENCE 2019), 2019, : 69 - 74