Fuzzy Optimization in Heterogeneous VANET Routing for Trusted Contention Window and Forwarder Selection

被引:0
作者
Visvesvaran, C. [1 ]
Karthikeyan, N. K. [2 ]
Vijayalakshmi, A. [3 ]
Sivasundhar, P. [1 ]
Ramamoorthy, V [1 ]
Rohith, P. A. [1 ]
机构
[1] Sri Krishna Coll Engn & Technol, Dept ECE, Coimbatore, Tamil Nadu, India
[2] Coimbatore Inst Technol, Dept IT, Coimbatore, Tamil Nadu, India
[3] Hindustan Coll Engn & Technol, Dept ECE, Coimbatore, Tamil Nadu, India
来源
2ND INTERNATIONAL CONFERENCE ON SUSTAINABLE COMPUTING AND SMART SYSTEMS, ICSCSS 2024 | 2024年
关键词
Fuzzy logic; Network Simulator 2 (NS-2); Adaptive Contention Window; Relay Selection Algorithm; Safety Alert Dissemination; VANETs (Vehicular Ad hoc Networks); NETWORKS;
D O I
10.1109/ICSCSS60660.2024.10625655
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study presents an advanced technique for broadcasting safety notifications within Vehicular Ad-hoc Networks (VANETs) using a trust-enhanced fuzzy inference mechanism, integrated at both the Medium Access Control (MAC) and network layers. The Trust-aware Contended Relay Selection Framework (TCRSF) approach optimizes the backoff duration a vehicle must observe before retransmitting data after a packet collision, as well as the intermediary node selection process, to better accommodate varying traffic conditions. The dynamic TCRSF model determines the optimal Contention Window (CW) size by considering factors such as link quality, network density, and vehicle speed. Additionally, the relay selection mechanism incorporates multiple parameters, including direction, speed variance, distance factor, and the Fast-Estimated Transmission Time (F-ETT) between the source vehicle and nearby vehicles within the broadcast range. Experimental results demonstrate that the TCRSF paradigm outperforms other methodologies, yielding improvements in network throughput, reductions in average packet latency, and enhanced reliability.
引用
收藏
页码:466 / 471
页数:6
相关论文
共 17 条
[1]  
Alzamzami O., 2023, P IEEE WIREL COMM NE, P263
[2]   Fuzzy Logic-Based Geographic Routing for Urban Vehicular Networks Using Link Quality and Achievable Throughput Estimations [J].
Alzamzami, Ohoud ;
Mahgoub, Imad .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2019, 20 (06) :2289-2300
[3]   VNDN-Fuzzy - A strategy to mitigate the forwarding interests broadcast storm problem in VNDN networks [J].
Barbosa Cunha, Ilane Karise ;
Celestino Junior, Joaquim ;
Fernandez, Marcial Porto ;
Patel, Ahmed ;
Monteiro, Maxwell E. .
2023 INTERNATIONAL CONFERENCE ON INFORMATION NETWORKING, ICOIN, 2023, :263-270
[4]  
Bindel S., 2016, ICST T MOBILE COMMUN, V2
[5]  
Bindel S, 2017, NETW TELECOMMUN SER, P185
[6]  
Brahmi N., 2009, P INT C WIR COMM MOB, P1310, DOI 10.1145/1582379.1582666
[7]   A Novel Coordinated Medium Access Control Scheme for Vehicular Ad Hoc Networks in Multichannel Environment [J].
Cao, Shengbin ;
Lee, Victor C. S. .
IEEE ACCESS, 2019, 7 :84333-84348
[8]   Fuzzy-Based Distributed Protocol for Vehicle-to-Vehicle Communication [J].
Hawbani, Ammar ;
Torbosh, Esa ;
Wang, Xingfu ;
Sincak, Peter ;
Zhao, Liang ;
Al-Dubai, Ahmed .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2021, 29 (03) :612-626
[9]  
Kamble Shridevi Jeevan, 2022, International Journal of Computer Networks and Applications, V9, P60, DOI [10.22247/ijcna/2022/211623, 10.22247/ijcna/2022/211623]
[10]  
Limouchi E., 2023, P IEEE S SER COMP IN, P1