A Self-Adaptive Back-Off Algorithm Based on Collision Probability and Expiration Probability of Beacons in VANET

Weiwan Liu; Zhijia Chen; Nanjie Liu; Hao Zhong; Haitao Zhao

doi:10.3969/j.issn.1000-0801.2014.03.017

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A Self-Adaptive Back-Off Algorithm Based on Collision Probability and Expiration Probability of Beacons in VANET

research and development | 更新时间：2024-06-05

- A Self-Adaptive Back-Off Algorithm Based on Collision Probability and Expiration Probability of Beacons in VANET
- Telecommunications Science Vol. 30, Issue 3, Pages: 94-99(2014)
- 作者机构：
  
  1. 南京邮电大学通信与信息工程学院南京 210003
  2. 南京邮电大学网络基因工程研究所南京 210003
  3. 国网上海市电力公司信息通信公司上海 200122
  4. 江苏有线数据网络有限公司南京 210003
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1000-0801.2014.03.017
  CLC：
- Published Online：2014-03，
  
  Published：20 March 2014
- 稿件说明：
移动端阅览
Weiwan Liu, Zhijia Chen, Nanjie Liu, et al. A Self-Adaptive Back-Off Algorithm Based on Collision Probability and Expiration Probability of Beacons in VANET[J]. Telecommunications science, 2014, 30(3): 94-99.
DOI：

Weiwan Liu, Zhijia Chen, Nanjie Liu, et al. A Self-Adaptive Back-Off Algorithm Based on Collision Probability and Expiration Probability of Beacons in VANET[J]. Telecommunications science, 2014, 30(3): 94-99. DOI： 10.3969/j.issn.1000-0801.2014.03.017.

摘要

为了提高车载自组织网络中信标消息的广播接收率，可通过建立马尔可夫链模型得出消息的碰撞概率和过期概率随最小竞争窗口的变化关系。根据上述结论提出一种根据当前车载网中过期消息数与预先设定门限值的相对大小关系而进行最小竞争窗口调整的退避算法CEB；对新提出的算法和原有的退避算法RBEB及BEB进行了仿真对比分析。仿真结果表明，所提出的退避算法相比于已有的退避算法，信标消息性能有了很大的提升。

Abstract

In order to improve the broadcast reception rate in VANET

the conclusion that the relationship between collision probability and minimum contention window size and the relationship between expiration probability and minimum window size were reached by building Markov model. According to this conclusion

a minimum contention window size adjustment back-off algorithm called CEB was proposed

it is on the basis of the relative size between the number of expiration beacons and pre-set threshold. Simulations were done to compare the performance of CEB

RBEB and BEB

and the results show that the performance of the new proposed algorithm is better than that of RBEB and BEB.

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references

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