Fuzzy logic-based VANET routing method to increase the QoS by considering the dynamic nature of vehicles

Abstract

Vehicular ad hoc network usually operates in various challenging situations like frequent topology changes, high vehicular mobility and the wide range of communication networks. Due to this it is very hard to maintain a higher data rate and also to achieve low latency during data communication. To overcome these problems, given the dynamic natures of all the vehicles in a given network in the proposed routing method, we have defined two fundamental parameters to determine the forwarding vehicle. The first parameter, which we developed, we call it “Channel quality factor (CQF)” or ‘Z’. The other parameter known as “Communication expiration time” or ‘T’ together with CQF is used in the present method to determine the forwarding vehicle. Fuzzy logic is also used to optimize various Quality of Service matrices. This proposed routing method involves two main parts; one is for forwarding Vehicle selection in the road based on the fuzzy logic. The second one is Road selection at the Road Junction to select the right path to reach the signal to the destination vehicle. The simulation results show that our proposed method performs well compare to other well-known protocols (MoZo, BRAVE, OFAODV) in terms of the average end to end delay, packet delivery ratio and control packet overhead, given any number of vehicles in a set of streets. While we are comparing with VEFR protocol, our proposed method shows higher performance in terms of average E2E delay and control packet overhead. However, it is interesting to see that VEFR gives \(\sim \)  5% better result than our proposed method when the number of vehicles in the streets are lower. But in the limit, when the number of vehicles reaches close to \(\sim \) 1900 the difference between the proposed method and method in VEFR goes to zero. At last we compare our proposed method with junction based two V2I protocols. In every cases, it shows better result even though we change the speed of the vehicles, beacon interval, channel data rate and transmission region.

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Acknowledgements

This work is done at the “Center of Innovation” at NIT Agartala, India. One of the author Dr. Bidyut K. Bhattacharyya is the founder of this innovation center.

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Correspondence to Arindam Debnath.

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Debnath, A., Basumatary, H., Dhar, M. et al. Fuzzy logic-based VANET routing method to increase the QoS by considering the dynamic nature of vehicles. Computing 103, 1391–1415 (2021). https://doi.org/10.1007/s00607-020-00890-x

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Keywords

  • Vehicular network
  • Fuzzy logic
  • Geographic routing
  • Intelligent transportation systems

Mathematics Subject Classification

  • 68