An adaptive intersection selection mechanism using ant Colony optimization for efficient data dissemination in urban VANET

Srivastava, Ankita; Prakash, Arun; Tripathi, Rajeev

doi:10.1007/s12083-020-00892-8

Cited by 27 publications

(18 citation statements)

References 27 publications

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“…It is interesting to see that at a higher number of vehicles, our packet delivery ratio approaches toward 100%, whereas they have a positive spike at around 250 number of vehicles and then right after that PDR values Fig. 19 PDR (%) versus number of vehicles, for AISM [44] and our proposed method Fig. 20 Average E2E delay versus number of vehicles, for AISM [44] and our proposed method reduces as the number of vehicles increases.…”

Section: Performance Analysis Of Our Proposed Methods By Comparing Witmentioning

confidence: 93%

“…20 Average E2E delay versus number of vehicles, for AISM [44] and our proposed method reduces as the number of vehicles increases. The maximum value for PDR for AISM [44] was found to occur at 250 vehicles. In Fig.…”

Section: Performance Analysis Of Our Proposed Methods By Comparing Witmentioning

confidence: 99%

“…In this section, we compare our proposed method with the junction node assisted two V2I (vehicle to infrastructure) routing methods, one is described in reference [43] and the other one is described in reference [44]. To simulate our proposed method and compare it with other V2I based methods, we have considered the parameters exactly same as used by the authors from [43,44]. In Fig.…”

Section: Performance Analysis Of Our Proposed Methods By Comparing Witmentioning

confidence: 99%

“…In Figs. 19 and 20, we show the packet delivery ratio (PDR in %) and Average End to End (E2E) Delay (in sec) of our proposed method and the method developed by authors from AISM [44]. The parameters used to simulate our method are the same as used by the authors from [44].…”

Section: Performance Analysis Of Our Proposed Methods By Comparing Witmentioning

confidence: 99%

“…19 and 20, we show the packet delivery ratio (PDR in %) and Average End to End (E2E) Delay (in sec) of our proposed method and the method developed by authors from AISM [44]. The parameters used to simulate our method are the same as used by the authors from [44]. It is interesting to see that at a higher number of vehicles, our packet delivery ratio approaches toward 100%, whereas they have a positive spike at around 250 number of vehicles and then right after that PDR values Fig.…”

Section: Performance Analysis Of Our Proposed Methods By Comparing Witmentioning

confidence: 99%

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

et al. 2021

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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 ∼ 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 ∼ 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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Section: Performance Analysis Of Our Proposed Methods By Comparing Witmentioning

confidence: 93%

Section: Performance Analysis Of Our Proposed Methods By Comparing Witmentioning

confidence: 99%

Section: Performance Analysis Of Our Proposed Methods By Comparing Witmentioning

confidence: 99%

Section: Performance Analysis Of Our Proposed Methods By Comparing Witmentioning

confidence: 99%

Section: Performance Analysis Of Our Proposed Methods By Comparing Witmentioning

confidence: 99%

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

et al. 2021

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Bio‐Inspired Routing in VANET

Aggarwal¹,

Gaba²,

Nagpal³

et al. 2021

Cloud and IoT‐Based Vehicular Ad Hoc Networks

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Internet of Vehicles and Intelligent Routing: A Survey-Based Study

Hassan

Attia

Rizk

2022

The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022)

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An adaptive intersection selection mechanism using ant Colony optimization for efficient data dissemination in urban VANET

Cited by 27 publications

References 27 publications

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

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

Bio‐Inspired Routing in VANET

Internet of Vehicles and Intelligent Routing: A Survey-Based Study

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