A stable clustering algorithm using the traffic regularity of buses in urban VANET scenarios

Tseng, Hsueh-Wen; Wu, Ruei-Yu; Lo, Ching‐Wen

doi:10.1007/s11276-019-02019-1

Cited by 24 publications

(14 citation statements)

References 32 publications

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“…Tseng et al [32] proposed a stable clustering algorithm called CATRB. This uses the traffic regularity of buses to improve stability by decreasing the number of CH changes.…”

Section: Hybrid (Dsrc/cellular Lte) Based Data Disseminationmentioning

confidence: 99%

Towards Optimal Dissemination of Emergency Messages in Internet of Vehicles: A Dynamic Clustering-Based Approach

Azzaoui

Korichi

Brik³

et al. 2021

Electronics

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In this paper, we target dissemination issues of emergency messages in a highly dynamic Internet of Vehicles (IoV) network. IoV is emerging as a new class of vehicular networks to optimize road safety as well as users’ comfort. In such a context, forwarding emergency messages through vehicle-to-vehicle communications (V2V) plays a vital role in enabling road safety-related applications. For instance, when an accident occurs, forwarding such information in real time will help to avoid other accidents in addition to avoiding congestion of network traffic. Thus, dissemination of emergency information is a major concern. However, on the one hand, vehicle density has increased in the last decade which may lead to several issues including message collisions, broadcast storm, and the problem of hidden nodes. On the other hand, high mobility of vehicles and hence dynamic changes of network topology result in failure of dissemination of emergency packets. To overcome these problems, we propose a new dissemination scheme of emergency packets by vehicles equipped with both DSRC and cellular LTE wireless communication capabilities. Our scheme is based on a dynamic clustering strategy, which includes a new cluster head selection algorithm to deal with the broadcast storm problem. Furthermore, our selection algorithm enables not only the election of the most stable vehicles as cluster heads, and hence their exploitation in forwarding the emergency information, but also the avoidance of packet collisions. We simulated our scheme in an urban environment and compared it with other data dissemination schemes. Obtained results show the efficiency of our scheme in minimizing collision and broadcast storm problems, while improving latency, packet delivery ratio and data throughput, as compared to other schemes.

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“…Tseng et al [32] proposed a stable clustering algorithm called CATRB. This uses the traffic regularity of buses to improve stability by decreasing the number of CH changes.…”

Section: Hybrid (Dsrc/cellular Lte) Based Data Disseminationmentioning

confidence: 99%

Towards Optimal Dissemination of Emergency Messages in Internet of Vehicles: A Dynamic Clustering-Based Approach

Azzaoui

Korichi

Brik³

et al. 2021

Electronics

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show abstract

“…To overcome this problem, the existence of an LTE base station is crucial in managing various aspects of the VANET networks such as maintaining the number of control packets, and assisting in the clustering and routing. According to [18], the importance of LTE base station is much higher than that of IEEE 802.11p for these tasks. Hence, the typical architecture of the VANETs combines both vehicle-to-vehicle V2V communications under IEEE802.11p and vehicle to infrastructure communications V2I under LTE base station.…”

Section: Literature Surveymentioning

confidence: 99%

“…In term of models: center-based [9] vs. distributed [2], in terms of the environment: highway [17] vs. urban [18], in terms of density: dense vs. sparse, in terms of speed, high speed vs. slow speed. Information used for VANETs clustering can be topology information, mobility information such as position, speed, and acceleration, contextual information such as type of vehicle, the intention of travel of driver; etc.…”

Section: Introductionmentioning

confidence: 99%

A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning and Extended Mobility Features for VANETs

Talib

Hassan

Alamery³

et al. 2020

IEEE Access

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VANETs clustering is an emerging research topic that serves in the intelligent transportation systems of today's technology. It aims at segmenting the moving vehicles in the road environment into subgroups named clusters, with cluster heads for enabling effective and stable routing. Most of the VANETs clustering approaches are based on distributed models which make the decision of clusters creation lacking the global view of the vehicle's distribution and mobility in the environment. However, the availability of the LTE and long ranges of base station motivated researchers recently to provide center-based approaches. Unlike existing center-based clustering approaches of VANETs, this article uses the road segmenting phase named grid partitioning before providing summarized information to the clustering center. Furthermore, it presents an integrated approach as a combination of all the clustering tasks including assigning, cluster head selection, removing, and merging. Evaluation of the proposed approach named center-based evolving clustering based on grid partitioning (CEC-GP) is proven superior from the perspective of efficiency, stability, and consistency. An improvement percentage of the efficiency in (CEC-GP) over the benchmarks Center based stable clustering (CBSC) and evolving data clustering algorithm (EDCA) is 65% and 394% respectively. INDEX TERMS vehicular ad hoc networks, VANETs clustering, Center-based clustering, evolving clustering, grid based-clustering.

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“…Most of the proposed clustering algorithms were designed to work in highway environment such as in [4, 18]. Recently, more attention was payed to consider more complicated and realistic environments such as urban [19, 20] and deserts [21]. Regarding the coverage of the cluster, multi‐hope clustering, as in [22, 23], is introduced to reduce the number of clusters (NoC) and generate wider clusters at the expense of the added complexity and cluster maintenance overhead, compared to traditional one‐hope clustering.…”

Section: Related Workmentioning

confidence: 99%

Bio‐inspired metaheuristic framework for clustering optimisation in VANETs

Alsuhli

Fahmy²,

Khattab³

2020

IET intell. transp. syst

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A stable clustering algorithm using the traffic regularity of buses in urban VANET scenarios

Cited by 24 publications

References 32 publications

Towards Optimal Dissemination of Emergency Messages in Internet of Vehicles: A Dynamic Clustering-Based Approach

Towards Optimal Dissemination of Emergency Messages in Internet of Vehicles: A Dynamic Clustering-Based Approach

A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning and Extended Mobility Features for VANETs

Bio‐inspired metaheuristic framework for clustering optimisation in VANETs

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