An intelligent path management in heterogeneous vehicular networks

被引:3
|
作者
Hapanchak, Vadym S. [2 ]
Costa, Antonio [1 ,2 ]
Pereira, Joao [2 ]
Nicolau, Maria Joao [1 ,3 ]
机构
[1] Univ Minho, Dept Informat, Braga, Portugal
[2] Univ Minho, ALGORITMI CTR, Braga, Portugal
[3] Univ Minho, Dept Informat Sistems, Braga, Portugal
关键词
V2X; MPTCP; Multipath; Vehicular heterogeneous networks; Network selection; Connected vehicles; SELECTION; HANDOVER; CHALLENGES; ATTRIBUTE; MPTCP; MODEL; TCP;
D O I
10.1016/j.vehcom.2023.100690
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Achieving reliable connectivity in heterogeneous vehicular networks is a challenging task, owing to rapid topological changes and unpredictable vehicle speeds. As vehicular communication demands continue to evolve, multipath connectivity is emerging as an important tool, which promises to enhance network interoperability and reliability. Given the limited coverage area of serving access technologies, frequent disconnections are to be expected as the vehicle moves. To ensure seamless communication in dynamic vehicular environments, an intelligent path management algorithm for Multipath TCP (MPTCP) has been proposed. The algorithm utilizes a network selection mechanism based on Fuzzy Analytic Hierarchy Process (FAHP), which dynamically assigns the most appropriate underlying network for each running application. The selection process takes into account multiple factors, such as path quality, vehicle mobility, and service characteristics. In contrast to existing solutions, our proposed method offers a dynamic and comprehensive approach to network selection that is tailored to the specific needs of each service to ensure that it is always paired with the optimal access technology. The results of the evaluation demonstrate that the proposed method is highly effective in maintaining service continuity during vertical handover. By tailoring the network selection to the specific needs of each application, our path manager is able to ensure optimal connectivity and performance, even in challenging vehicular environments, delivering a better user experience, with more reliable connections, and smoother data transfers.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] An Intelligent Congestion Avoidance Mechanism Based on Generalized Regression Neural Network for Heterogeneous Vehicular Networks
    Falahatraftar, Farnoush
    Pierre, Samuel
    Chamberland, Steven
    IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 8 (04): : 3106 - 3118
  • [32] Poster: Towards 2-Hop Neighbor Management for Heterogeneous Vehicular Networks
    Turcanu, Ion
    Kim, Minsuk
    Klingler, Florian
    2020 IEEE VEHICULAR NETWORKING CONFERENCE (VNC), 2020,
  • [33] Multipath TCP Path Scheduling Optimization Based on Q-Learning in Vehicular Heterogeneous Networks
    Zhao, Haitao
    Zhang, Mengkang
    Yu, Hongsu
    Mao, Tianqi
    Zhu, Hongbo
    2018 10TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP), 2018,
  • [34] Multi-objective Optimization for Network Resource Management in Heterogeneous Vehicular Networks
    Dai, Penglin
    Liu, Kai
    Wu, Xiao
    Xing, Huanlai
    Lee, Victor C. S.
    2019 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2019,
  • [35] Heterogeneous Vehicular Networks for Social Networks:Requirements and Challenges
    YANG Haojun
    ZHENG Kan
    LEI Lei
    XIANG Wei
    ZTECommunications, 2016, 14 (03) : 29 - 35
  • [36] Heterogeneous Algorithm for Efficient-Path Detection and Congestion Avoidance for a Vehicular-Management System
    Noussaiba, Melaouene
    Razaque, Abdul
    Rahal, Romadi
    SENSORS, 2023, 23 (12)
  • [37] Intelligent Clustering in Vehicular ad hoc Networks
    Aadil, Farhan
    Khan, Salabat
    Bajwa, Khalid Bashir
    Khan, Muhammad Fahad
    Ali, Asad
    KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2016, 10 (08): : 3512 - 3528
  • [38] Fault Tree Analysis for the Intelligent Vehicular Networks
    Dabboussi, Abdallah
    Kouta, Raed
    Gaber, Jaafar
    Wack, Maxime
    El Hassan, Bachar
    Nachabeh, Lina
    2018 IEEE MIDDLE EAST AND NORTH AFRICA COMMUNICATIONS CONFERENCE (MENACOMM), 2018, : 200 - 205
  • [39] SDN Architecture for Intelligent Vehicular Sensors Networks
    Sadio, Ousmane
    Ngom, Ibrahima
    Lishou, Claude
    2018 UKSIM-AMSS 20TH INTERNATIONAL CONFERENCE ON COMPUTER MODELLING AND SIMULATION (UKSIM), 2018, : 139 - 144
  • [40] Intelligent systems for heterogeneous networks
    Tsai, Chun-Wei
    Rawat, Priyanka
    Chiang, Ming-Chao
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2017, 85 : 1 - 3