A Systematic Classification of Routing In Vehicular Ad Hoc Networks

,; Kad*, Sandeep; Banga, Vijay Kumar; ,

doi:10.35940/ijeat.f8779.088619

Cited by 4 publications

(3 citation statements)

References 76 publications

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“…These technologies can facilitate communication between the vehicle nodes by using centralized infrastructure or ad hoc methods. The interconnection and interoperability requirements are addressed via communication standards, which enables systems such as Dedicated Short Range Communication using WAVE to be applied [33].…”

Section: Related Workmentioning

confidence: 99%

Effect of Waiting Time and Number of Slots on Vehicular Networking Employing Slotted ALOHA Protocol

2024

IJIES

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This work investigates through simulation effect of waiting time and number of slots on the effectiveness of using Slotted ALOHA in vehicular connectivity as a random access technique. The objective is to reach optimum level of throughput under the vehicular dynamic environment. The presented work proposes to concentrate on waiting time as a controlling parameter that can be used in an adaptive manner to enable throughput optimization in response to changing vehicular density. The work proved through MATLAB simulation the importance of waiting time parameter in controlling number of delivered frames and throughput. The results show that based on the exponential relationship between throughput and data traffic, there is a logarithmic relationship between data traffic and waiting time, which complements another logarithmic relationship between throughput and waiting time. The simulation also shows that there is an inverse relationship between throughput and data traffic as a function of set waiting time. The simulation shows that there is an exponential relationship between waiting time and maximum number of delivered frames. The work shows that a linear region of operating Slotted ALOHA can be specified, such that an optimum and dynamically adjusted waiting time is set with overall effect on number of slots and throughput. The dynamic shape function of the curve correlating waiting time to available number of slots is mathematically modelled and differentially controlled, thus an optimizing and controlling algorithm is produced, which improves significantly the conventional ALOHA performance and has an advantage over other used ALOHA derivatives, in that it concentrates on available slots and waiting time, which greatly contributes towards reduction in collisions and improving of throughput.

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Section: Related Workmentioning

confidence: 99%

Effect of Waiting Time and Number of Slots on Vehicular Networking Employing Slotted ALOHA Protocol

2024

IJIES

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“…Where; 𝜴 = ( 𝜽 𝝓+𝝋+𝜽 ) and 𝜻 = (𝝓 + 𝝋 + 𝜽) Also, Eq. ( 15) can be re-written as in equation (20). Thus, the throughput is modulated by the dynamically changing parameters in Eqs.…”

Section: Effect Of Machine Time (Tm)mentioning

confidence: 99%

Adaptive Vehicular Communication using ALOHA CSMA with Modified Logistic Function (ALOHAMLF)

2023

IJIES

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The objective of this work is to mathematically model vehicular connectivity using ALOHA base function with modified logistic function as an adaptive control function. The focus of this work is to utilize the ALOHA protocol as a carrier sensing multiple access technique and add to it an intelligent part, which is the modified logistic function (MLF) to enable adaptive communication channel. The work correlates three time based parameters related to vehicle, communication, and human driver, which are associated with connected vehicles (driver response time, machine processing time, and channel communication time). The mathematical model showed that throughput for autonomous and connected vehicles is much higher than that for connected vehicles due to the elimination of human time factor, together with the evident low response time from sensors, electronics, and communication. In addition, a more stable connectivity is established if human element is not part of the model, as this eliminates both uncertainty and lengthy human response time. The ALOHA function role is to enable continuous tries by each node (vehicle) to establish communication with probability related to availability of communication channel and a back off functionality in case of collision. The proposed model provides dynamic and adaptive technique to adjust time slots using the continuous change in the vehicular connectivity environment, which affects the presented time parameters, thus changing frames delivery pattern and time slots utilization. The presented approach, supports better and more efficient use of communication channel, particularly in the case of autonomous and connected vehicles. It also, highlights through comparison the inhibitory effect driver actions can have on safe driving, through time delay, and low communication channel utilization. In addition, the work also focusses on the effect of processing time for sensors and electronics, which also have negative effect on channel usage and effectiveness, if there is a functional problem.

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“…By increasing connectivity times with better signal quality and improving routing performance due to scalability, clustering can significantly contribute to more efficient bandwidth utilization, dependable message exchange and delivery. As a result of grouping traveling vehicles into clusters, network performance can be greatly improved [1], [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Vehicular Communication using Gaussian Interpolation of Cluster Head Selection (GI-CHS)

Iskandarani¹

2022

IJACSA

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Decentralized and centralized vehicular communication is investigated in this work using Gaussian interpolation function with cluster head (CH) selection technique. The work uncovered that the best communication approach is to use both centralized and decentralized vehicular communication as combining them will achieve a much more uniform results as a function of communication radius values and vehicular speed. It is also found that vehicular speed contributes negatively to the efficiency of data communication if the relative speed of the vehicles to the communication radius is limited by their ratios. Mathematical expression is presented that relates probability of successful transmission to communication radius for both centralized and decentralized techniques with data proving the importance of the spread parameter within the Gaussian interpolation in a tabulated form, and explained to prove the adaptability of the function used. It is also shown in this work that weights affecting CH selection, thus using Gaussian interpolation is proved to be important as a weighting function in an a adaptive and dynamic vehicular ad-hoc networks (VANETS) covering both vehicle to vehicle (V2V), and vehicle to infrastructure (V2I) communication through cluster head selection.

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A Systematic Classification of Routing In Vehicular Ad Hoc Networks

Cited by 4 publications

References 76 publications

Effect of Waiting Time and Number of Slots on Vehicular Networking Employing Slotted ALOHA Protocol

Effect of Waiting Time and Number of Slots on Vehicular Networking Employing Slotted ALOHA Protocol

Adaptive Vehicular Communication using ALOHA CSMA with Modified Logistic Function (ALOHAMLF)

Dynamic Vehicular Communication using Gaussian Interpolation of Cluster Head Selection (GI-CHS)

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