scholarly journals Dynamic Contention Window based Safety-Application Model for Vehicular Ad-hoc Networks

2018 ◽  
Vol 132 ◽  
pp. 421-428
Author(s):  
Poonam Verma ◽  
Neeta Singh ◽  
Riya Lamba ◽  
Somendra Prakash Singh
Author(s):  
Hayder M. Amer ◽  
Ethar Abduljabbar Hadi ◽  
Lamyaa Ghaleb Shihab ◽  
Hawraa H. Al Mohammed ◽  
Mohammed J. Khami

Technology such as vehicular ad hoc networks can be used to enhance the convenience and safety of passenger and drivers. The vehicular ad hoc networks safety applications suffer from performance degradation due to channel congestion in high-density situations. In order to improve vehicular ad hoc networks reliability, performance, and safety, wireless channel congestion should be examined. Features of vehicular networks such as high transmission frequency, fast topology change, high mobility, high disconnection make the congestion control is a challenging task. In this paper, a new congestion control approach is proposed based on the concept of hybrid power control and contention window to ensure a reliable and safe communications architecture within the internet of vehicles network. The proposed approach performance is investigated using an urban scenario. Simulation results show that the network performance has been enhanced by using the hybrid developed strategy in terms of received messages, delay time, messages loss, data collision and congestion ratio.


Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6092
Author(s):  
Zhonghui Pei ◽  
Xiaojun Wang ◽  
Zhen Lei ◽  
Hongjiang Zheng ◽  
Luyao Du ◽  
...  

Beacon messages and emergency messages in vehicular ad hoc networks (VANETs) require a lower delay and higher reliability. The optimal MAC protocol can effectively reduce data collision in VANETs communication, thus minimizing delay and improving reliability. In this paper, we propose a Q-learning MAC protocol based on detecting the number of two-hop neighbors. The number of two-hop neighbors in highway scenarios is calculated with very little overhead using the beacon messages and neighbor locations to reduce the impact of hidden nodes. Vehicle nodes are regarded as agents, using Q-learning and beacon messages to train the near-optimal contention window value of the MAC layer under different vehicle densities to reduce the collision probability of beacon messages. Furthermore, based on the contention window value after training, a multi-hop broadcast protocol combined with contention window adjustment for emergency messages in highway scenarios is proposed to reduce forwarding delay and improve forwarding reliability. We use the trained contention window value and the state information of neighboring vehicles to assign an appropriate forwarding waiting time to the forwarding node. Simulation experiments are conducted to evaluate the proposed MAC protocol and multi-hop broadcast protocol and compare them with other related protocols. The results show that our proposed protocols outperform the other related protocols on several different evaluation metrics.


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