A Unified Framework of Clustering Approach in Vehicular Ad Hoc Networks

Ren, Mengying; Zhang, Jun; Khoukhi, Lyes; Labiod, Houda; Vèque, Véronique

doi:10.1109/tits.2017.2727226

Cited by 82 publications

(40 citation statements)

References 32 publications

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“…The existing clustering approaches differ in cluster leadership in terms of the number of CHs and the way they are selected. Most of the schemes suffice with one CH for each cluster such as in [14,16,17]. Despite the simplicity of this approach, reclustering will be an inevitable once the CH resigns or loses its suitability to continue as a CH.…”

Section: Vanet Clustering Algorithmsmentioning

confidence: 99%

“…The popular selection methods can be classified into competition-based and comparison-based CH selection methods. UFC and TB [16,23] are some examples of clustering algorithm that use competition to select the CH. A backoff timer is set by each vehicle separately.…”

Section: Vanet Clustering Algorithmsmentioning

confidence: 99%

“…A backoff timer is set by each vehicle separately. The timer value is usually calculated depending on some metrics [16,23] or is set randomly as also proposed in [16]. The vehicle that firstly broadcasts a CH announcement wins the competition and becomes the CH.…”

Section: Vanet Clustering Algorithmsmentioning

confidence: 99%

See 2 more Smart Citations

Double-Head Clustering for Resilient VANETs

Alsuhli

Khattab

Fahmy

2019

Wireless Communications and Mobile Computing

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Scalability and the highly dynamic topology of Vehicular Ad Hoc Networks (VANETs) are the biggest challenges that slow the roll-out of such a promising technology. Adopting an effective VANET clustering algorithm can tackle these issues in addition to benefiting routing, security and media access management. In this paper, we propose a general-purpose resilient double-head clustering (DHC) algorithm for VANET. Our proposed approach is a mobility-based clustering algorithm that exploits the most relevant mobility metrics such as vehicle speed, position, and direction, in addition to other metrics related to the communication link quality such as the link expiration time (LET) and the signal-to-noise ratio (SNR). The proposed algorithm has enhanced performance and stability features, especially during the cluster maintenance phase, through a set of procedures developed to achieve these objectives. An extensive evaluation methodology is followed to validate DHC and compare its performance with another algorithm using different existing and newly proposed evaluation metrics. These metrics are analyzed under various mobility scenarios, vehicle densities, and radio channel models such as log-normal shadowing and two-ray ground loss with and without Nakagami-m fading model. The proposed algorithm DHC has proven its ability to be more stable and efficient under different simulation scenarios.

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Section: Vanet Clustering Algorithmsmentioning

confidence: 99%

Section: Vanet Clustering Algorithmsmentioning

confidence: 99%

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Double-Head Clustering for Resilient VANETs

Alsuhli

Khattab

Fahmy

2019

Wireless Communications and Mobile Computing

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“…In a graph or network, clusters are typically groups of vertices with a higher probability of connecting to each other than to members of other groups, although other patterns are possible [2]. Clusters have many application scenarios in the Internet of Things [3], including sensor networks [4], vehicular ad hoc networks [5]- [7], and in-vehicle networks [8]- [10]. Community detection can be viewed as a problem of graph clustering in which each community corresponds to a cluster in the graph [11], [12].…”

Section: A Backgroundmentioning

confidence: 99%

Local Expansion and Optimization for Higher-Order Graph Clustering

Cai

et al. 2019

IEEE Internet Things J.

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Graph clustering aims to identify clusters that feature tighter connections between internal nodes than external nodes. We noted that conventional clustering approaches based on a single vertex or edge cannot meet the requirements of clustering in a higher-order mixed structure formed by multiple nodes in a complex network. Considering the above limitation, we are aware of the fact that a clustering coefficient can measure the degree to which nodes in a graph tend to cluster, even if only a small area of the graph is given. In this study, we introduce a new cluster quality score, i.e., the local motif rate, which can effectively respond to the density of clusters in a higherorder graph. We also propose a motif-based local expansion and optimization algorithm (MLEO) to improve local higher-order graph clustering. This algorithm is a purely local algorithm and can be applied directly to higher-order graphs without conversion to a weighted graph, thus avoiding distortion of the transform. In addition, we propose a new seed-processing strategy in a higher-order graph. The experimental results show that our proposed strategy can achieve better performance than the existing approaches when using a quadrangle as the motif in the LFR network and the value of the mixing parameter µ exceeds 0.6.

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“…Assumptions 1 and 3 are practical in a vehicular environment, which have been mentioned by a lot of authors. () Assumption 2 is made because of constraint for deploying roadside infrastructure from the economic perspective. Thus, the proposed scheme is generally concentrated on V2V communication.…”

Section: Assumptions and System Modelmentioning

confidence: 99%

A stable and reliable data dissemination scheme based on intelligent forwarding in VANETs

Chahal

Harit

2018

Int J Communication

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Vehicular ad hoc networks (VANETs) have gained incredible attention because of their applications in safety, commercial uses, and traffic management. However, the dynamic topology changes caused by the high speed of vehicles raise many challenges for the effective data dissemination in vehicular applications.In this paper, with the objective to solve the problem of frequent disconnection during data delivery, we propose a novel, intelligent forwarding-based stable and reliable data dissemination scheme. First, link stability is described mathematically, by which vehicle chooses the next forwarding node. Then, a greedy algorithm is presented to transmit the data from source to destination. A separate recovery algorithm is also designed to resolve the intermediate link breakage problem. The performance of the proposed method is analyzed by performing extensive network and traffic simulations with respect to various indexes such as latency, packet delivery ratio (PDR), and throughput. Compared with the state-of-the-art protocols, the proposed method under varying density improves the average PDR and throughput by 31.55% and 25.30%, respectively. KEYWORDS greedy forwarding, link duration, stability, VANET INTRODUCTIONVehicular ad hoc networks (VANETs) have emerged as an integral part of intelligent transportation system (ITS) for effective data transmission in the past few years. The inter-vehicle and roadside communication networks of VANETs have gained importance because of its usage in many applications all over the world. Road safety, traffic control, and infotainment are the promising applications of vehicular communication. Vehicle and roadside unit (RSU) act as intelligent devices for data collection from the environment by using effective routing protocols and then transmitting the data to other devices connected to the Internet and cloud. VANETs support two distinct communication scenarios: vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. In V2V, vehicles exchange information with one another, and in V2I, vehicles uses information provided by nearest roadside components. The architecture of vehicular communication is shown in Figure 1. The amendment to the IEEE 802.11 standard, ie, IEEE 802.11p, pertains to vehicular communications. 1 The standard comprises the Physical (PHY) and Media Access Control (MAC) protocols for Wireless Access in Vehicular Environment (WAVE). 2 The higher layer protocols are built on the IEEE 1609 standard. In 2003, Federal Communications Commission (FCC) proposed a dedicated short-range communications (DSRC) system with the allocation of 75 MHz of spec-Int J Commun Syst. 2019;32:e3869. wileyonlinelibrary.com/journal/dac FIGURE 1 Vehicular ad hoc network architecture. RSU indicates roadside unittrum for vehicular emergency warning messages and other applications of VANETs. In Europe, CAR 2 CAR Communication Consortium (C2C-CC) was founded as a vehicle manufacturer organization to increase efficiency and road traffic safety using inter-vehicle message excha...

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A Unified Framework of Clustering Approach in Vehicular Ad Hoc Networks

Cited by 82 publications

References 32 publications

Double-Head Clustering for Resilient VANETs

Double-Head Clustering for Resilient VANETs

Local Expansion and Optimization for Higher-Order Graph Clustering

A stable and reliable data dissemination scheme based on intelligent forwarding in VANETs

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