Channel capacity optimization scheme for safety applications in vehicular ad hoc networks

被引:0
作者
Sharma, Swati [1 ]
Chahal, Manisha [2 ]
Harit, Sandeep [1 ]
Kumar, Neeraj [3 ]
机构
[1] Punjab Engn Coll, Dept Comp Sci & Engn, Chandigarh, India
[2] MPSTME NMIMS, Dept Comp Engn, Mumbai, Maharashtra, India
[3] Univ Petr & Energy Studies, Dept Comp Sci, Dehra Dun, Uttarakhand, India
关键词
congestion control; decentralized congestion control; MAC layer; VANETs; water filling algorithm; CONGESTION CONTROL; DATA DISSEMINATION; PROTOCOLS; FRAMEWORK; SECURE; POWER;
D O I
10.1002/dac.5280
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Vehicular ad hoc networks (VANETs) have attracted significant attention due to their safety, traffic management, and infotainment applications. However, vehicular communication suffers from network congestion caused by high vehicle density, which raises numerous challenges for efficiently disseminating emergency messages in vehicular safety applications. This paper aims to solve the problem of capacity optimization of the control channel (CCH) during the delivery of emergency messages. Hence, we propose a novel channel capacity optimization scheme for safety application (CCOSSA). The performance of the CCOSSA scheme is evaluated by performing comprehensive traffic and network simulations regarding various parameters such as the probability of reception, channel busy time (CBT) ratio, and average delay. CCOSSA scheme is compared with the state-of-the-art schemes under varying vehicle density and distance from the source in which the proposed scheme shows an improvement in the performance.
引用
收藏
页数:23
相关论文
共 57 条
  • [31] Reliable congestion control mechanism for safety applications in urban VANETs
    Li, Wenfeng
    Song, Wuli
    Lu, Qiang
    Yue, Chao
    [J]. AD HOC NETWORKS, 2020, 98
  • [32] Interval Type-2 Fuzzy Analysis and Comprehensive Evaluation for Neonatal Pathological Jaundice
    Mo, Hong
    Yang, Chun
    Wang, Xiao
    Wang, Fei-Yue
    [J]. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2022, 9 (05) : 1542 - 1551
  • [33] Nahar K., 2019, P INT C SUSTAINABLE, P1437
  • [34] Distributed α-Fair Transmit Power Adaptation Based Congestion Control in VANET
    Navdeti, Chandrakant
    Giri, Chandan
    Banerjee, Indrajit
    [J]. ICDCN '19: PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING AND NETWORKING, 2019, : 253 - 260
  • [35] Blockchain-Enabled Intelligent Transportation Systems: A Distributed Crowdsensing Framework
    Ning, Zhaolong
    Sun, Shouming
    Wang, Xiaojie
    Guo, Lei
    Guo, Song
    Hu, Xiping
    Hu, Bin
    Kwok, Ricky Y. K.
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2022, 21 (12) : 4201 - 4217
  • [36] Intelligent resource allocation in mobile blockchain for privacy and security transactions: a deep reinforcement learning based approach
    Ning, Zhaolong
    Sun, Shouming
    Wang, Xiaojie
    Guo, Lei
    Wang, Guoyin
    Gao, Xinbo
    Kwok, Ricky Y. K.
    [J]. SCIENCE CHINA-INFORMATION SCIENCES, 2021, 64 (06)
  • [37] PERCEPTION-RESPONSE TIME TO UNEXPECTED ROADWAY HAZARDS
    OLSON, PL
    SIVAK, M
    [J]. HUMAN FACTORS, 1986, 28 (01) : 91 - 96
  • [38] Dispatch of UAVs for Urban Vehicular Networks: A Deep Reinforcement Learning Approach
    Oubbati, Omar Sami
    Atiquzzaman, Mohammed
    Baz, Abdullah
    Alhakami, Hosam
    Ben-Othman, Jalel
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (12) : 13174 - 13189
  • [39] A statistical approach for enhancing security in VANETs with efficient rogue node detection using fog computing
    Paranjothi, Anirudh
    Atiquzzaman, Mohammed
    [J]. DIGITAL COMMUNICATIONS AND NETWORKS, 2022, 8 (05) : 814 - 824
  • [40] Resource Allocation for Vehicle-to-Infrastructure Communication Using Directional Transmission
    Pyun, Sung-Yeop
    Lee, Woongsup
    Cho, Dong-Ho
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 17 (04) : 1183 - 1188