Coalitional Game Theoretical Approach for VANET Clustering to Improve SNR

Sulistyo, Selo; Alam, Sahirul; Adrian, Ronald

doi:10.1155/2019/4573619

Cited by 10 publications

(20 citation statements)

References 24 publications

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“…A modified version of AddP is later proposed as Optimal Adaptive data dissemination Protocol OAddP [105], which deals with different traffic flow, utilizing prediction-based decision-making schemes to generate clusters and disseminate data. Selo et al proposed a distributed approach based on Coalitional Game Clustering (CGC) [106] that allows every vehicle to make a distributed cluster with other vehicles based on coalition value. This value is based on connection lifetime and speed difference among vehicles.…”

Section: Distributed Clusteringmentioning

confidence: 99%

Data collection protocols for VANETs: a survey

Gillani

Niaz

Farooq

et al. 2022

Complex Intell. Syst.

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We live in the era of Intelligent Transport Systems (ITS), which is an extension of Vehicular AdHoc Networks (VANETs). In VANETs, vehicles act as nodes connected with each other and sometimes with a public station. Vehicles continuously exchange and collect information to provide innovative transportation services; for example, traffic management, navigation, autonomous driving, and the generation of alerts. However, VANETs are extremely challenging for data collection, due to their high mobility and dynamic network topologies that cause frequent link disruptions and make path discovery difficult. In this survey, various state-of-the-art data collection protocols for VANETs are discussed, based on three broad categories, i.e., delay-tolerant, best-effort, and real-time protocols. A taxonomy is designed for data collection protocols for VANETs that is essential to add precision and ease of understandability. A detailed comparative analysis among various data collection protocols is provided to highlight their functionalities and features. Protocols are evaluated based on three parametric phases. First, protocols investigation based on six necessary parameters, including delivery and drop ratio, efficiency, and recovery strategy. Second, a 4-D functional framework is designed to fit most data collection protocols for quick classification and mobility model identification, thus eradicating the need to read extensive literature. In the last, in-depth categorical mapping is performed to deep dive for better and targeted interpretation. In addition, some open research challenges for ITS and VANETs are discussed to highlight research gaps. Our work can thus be employed as a quick guide for researchers to identify the technical relevance of data collection protocols of VANETs.

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Section: Distributed Clusteringmentioning

confidence: 99%

Data collection protocols for VANETs: a survey

Gillani

Niaz

Farooq

et al. 2022

Complex Intell. Syst.

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“…Typically, its position is at the border of clusters. TCH is a special type of CH with a short lifespan. It is used in certain protocols in the literature to ensure an effective choice of primary CH. TCM is a special type of CM with a short lifespan. It is utilized in some algorithms to increase the stability of the clusters and decrease the rate of overlap between clusters. SCH is a passive CH, which will replace the active CH, in case it becomes unavailable or leaves the cluster.…”

Section: Clustering In Vanets: An Overviewmentioning

confidence: 99%

“…• TCH is a special type of CH with a short lifespan. It is used in certain protocols in the literature [17][18][19] to ensure an effective choice of primary CH. • TCM is a special type of CM with a short lifespan.…”

Section: Cluster Structurementioning

confidence: 99%

Survey on vehicular ad hoc networks clustering algorithms: Overview, taxonomy, challenges, and open research issues

Senouci

Harous

Aliouat

2020

Int J Communication

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Summary Vehicular ad hoc networks (VANETs) have recently attracted considerable attention owing to their wide range of applications. However, there are several challenges, such as mobility, routing, scalability, quality of services, and security. Clustering is an important control mechanism in high‐mobility networks and has been verified to be a promising approach in VANETs as well, as it ensures a basic level of network performance. Accordingly, several clustering algorithms have been proposed for these networks, and different protocols typically focus on various performance metrics. In this study, we provide a thorough review of clustering algorithms in VANETs. First, we present background material regarding the clustering process. Secondly, we propose a new taxonomy that categorizes clustering algorithms in VANETs based on different design aspects and provides a description of the algorithms in each category. Thirdly, an analysis of the algorithms in each category is provided according to various comparison metrics. Fourthly, we highlight the main challenges for each category and discuss some open research issues. Finally, we provide a general comparison of different clustering algorithms according to selected key parameters. Thus, this study provides a more thorough understanding of VANET clustering algorithms and the research trends in this area.

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“…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. Hence, having an LTE to serve in the clustering which has been called a center-based clustering based on V2I communications [41] . In the work of [42] a center-based VANETs clustering is proposed based on both modified k-means and Floyd-Warshall algorithm.…”

Section: Literature Surveymentioning

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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Coalitional Game Theoretical Approach for VANET Clustering to Improve SNR

Cited by 10 publications

References 24 publications

Data collection protocols for VANETs: a survey

Data collection protocols for VANETs: a survey

Survey on vehicular ad hoc networks clustering algorithms: Overview, taxonomy, challenges, and open research issues

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

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