Toward Strongley Connected Clustering Structure in Vehicular Ad Hoc Networks

Rawshdeh, Zaydoun Y.; Mahmud, Syed Masud

doi:10.1109/vetecf.2009.5378799

Cited by 45 publications

(24 citation statements)

References 4 publications

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“…For all simulation scenarios, the Δv th = s, e.g., for μ = 70 km/h and s = 21 km/h, the Δv th = 21. The performance of different Δv th values can be found in [29].…”

Section: The Mobility Modelmentioning

confidence: 99%

A novel algorithm to form stable clusters in vehicular ad hoc networks on highways

Rawashdeh

Mahmud

2012

J Wireless Com Network

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194

130

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Clustering in vehicular ad hoc networks (VANET) is one of the control schemes used to make VANET global topology less dynamic. Many of the VANET clustering algorithms are derived from mobile ad hoc networks (MANET). However, VANET nodes are characterized by their high mobility, and the existence of VANET nodes in the same geographic proximity does not mean that they exhibit the same mobility patterns. Therefore, VANET clustering schemes should take into consideration the degree of the speed difference among neighboring nodes to produce relatively stable clustering structure. In this paper, we introduce a new clustering technique suitable for the VANET environment on highways with the aim of enhancing the stability of the network topology. This technique takes the speed difference as a parameter to create relatively stable cluster structure. We also developed a new multi-metric algorithm for cluster-head elections. A simulation was conducted to evaluate our method and compare it with the most commonly used clustering methods. The simulation results show that our technique provides more stable cluster structure on the locale scale which results in a more stable network structure on the global scale. The proposed technique reduces the average number of clusters changed per vehicle by 34-46%, and increases the average cluster lifetime by 20-48% compared to the existing techniques.

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“…For all simulation scenarios, the Δv th = s, e.g., for μ = 70 km/h and s = 21 km/h, the Δv th = 21. The performance of different Δv th values can be found in [29].…”

Section: The Mobility Modelmentioning

confidence: 99%

A novel algorithm to form stable clusters in vehicular ad hoc networks on highways

Rawashdeh

Mahmud

2012

J Wireless Com Network

Self Cite

194

130

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“…These events are some vehicles leaving the cluster and/or some vehicles entering the cluster [19]. Relative speed level among vehicles can helps in keeping the vehicles in a cluster and reducing the probability of moving out of that cluster [20], [13], tried to create new reliable cluster. They depended on the velocity difference among vehicles, vehicles direction and vehicles location in their clustering formation process.…”

Section: Vehicles Relative Velocitymentioning

confidence: 99%

A Novel Stable Clustering Approach based on Gaussian Distribution and Relative Velocity in VANETs

Talib¹,

Hassan²,

Hussin³

et al. 2018

ijacsa

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“…With regard to increasing number of cars that potentially leads to some accidents, [21] proposed an algorithm considering the speed, movement direction, and the location of each node to specify the cluster configurations. The main objective of the algorithm is to reduce the number of clusters and increase each cluster stability and longevity.…”

Section: Literature Reviewmentioning

confidence: 99%

An Adaptive Multi-hop Clustered Voting to Improve the Message Trust in Vehicular Ad-hoc Networks

Mirzaei

Mollamotalebi

2018

IJATES

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Abstract-The Vehicular Ad-hoc Network (VANET) is used in intelligent transportation systems to make communication between vehicles and make appropriate decisions with regard to road or traffic conditions. Some main research issues in VANETs are unreliability in communication, delay/precision of decision making, information overheads, and handling the nodes dynamicity. This paper aimed to provide an efficient voting method to improve the reliability of decision making for message voting. It also reduces the voting delay and network information overhead. The proposed method is simulated in NS2. The experimental results indicated that the proposed methods decision making precision is improved between 6% and 30% compared to similar methods in the literature, under conditions such as traffic amount, number of nodes and operation period time. It also reduces the number of transferred packets between 1% and 9% in different environmental conditions.

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Toward Strongley Connected Clustering Structure in Vehicular Ad Hoc Networks

Cited by 45 publications

References 4 publications

A novel algorithm to form stable clusters in vehicular ad hoc networks on highways

A novel algorithm to form stable clusters in vehicular ad hoc networks on highways

A Novel Stable Clustering Approach based on Gaussian Distribution and Relative Velocity in VANETs

An Adaptive Multi-hop Clustered Voting to Improve the Message Trust in Vehicular Ad-hoc Networks

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