MCA-V2I: A Multi-hop Clustering Approach over Vehicle-to-Internet communication for improving VANETs performances

Senouci, Oussama; Aliouat, Zibouda; Harous, Saad

doi:10.1016/j.future.2019.02.024

Cited by 72 publications

(40 citation statements)

References 18 publications

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“…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. It has been used in previous researches to improve clusters stability.…”

Section: Clustering In Vanets: An Overviewmentioning

confidence: 99%

“…According to the available literature, there are two main cluster formation strategies: distributed and centralized strategies. Distributed strategy: Many clustering protocols have used this strategy to form the clusters. After receiving the necessary information from the neighborhood, each node in the network seeks its affiliation locally.…”

Section: Clustering In Vanets: An Overviewmentioning

confidence: 99%

“…The average CM lifetime is calculated by dividing the total CM lifetime by the total number of state changes from CM to another state. CH change number : It represents the rate of state changes from CH to another state. Cluster number : It is the number of clusters constructed during network operation. Small values improve the efficiency of the clustering algorithm. Average size of cluster : It is the average number of CM nodes managed by a CH during the total network operation time. Time complexity: It represents the time required to perform a valid clusterre‐organization after a change in network topology. Message delivery latency: Refers to the average delay or time required for a message to be transmitted from a source to a destination …”

Section: Clustering In Vanets: An Overviewmentioning

confidence: 99%

See 2 more Smart Citations

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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Section: Clustering In Vanets: An Overviewmentioning

confidence: 99%

Section: Clustering In Vanets: An Overviewmentioning

confidence: 99%

Section: Clustering In Vanets: An Overviewmentioning

confidence: 99%

See 1 more Smart Citation

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

Senouci

Harous

Aliouat

2020

Int J Communication

Self Cite

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“…This method can help with cluster stability, however, the affinity algorithm involves multiple iterative loops, which increase the cluster formation time and, consequently, produce more delay. In [25], the authors propose a multi-hop clustering scheme based on breadth-first search algorithm (BFS) to improve network stability and efficiency. The key metric of this scheme is the relative velocity and distance to structure a stable cluster.…”

Section: B Related Workmentioning

confidence: 99%

“…• We tend to build the clusters based on mobility metrics [25], [29], [30] together with our proposed L S T metric, which can maintain the cluster for a longer time, in order to reduce the communication overhead and achieve a high PDR in a highway scenario. • To tackle the broadcast storm problem, we select a relay vehicle by considering L S T , and thereby boost the PDR with acceptable end-to-end delay in high-density networks.…”

Section: Novelty and Contributionsmentioning

confidence: 99%

RBO-EM: Reduced Broadcast Overhead Scheme for Emergency Message Dissemination in VANETs

Ullah

Abbas

et al. 2020

IEEE Access

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Effective information dissemination constitutes the cornerstone of communication in Vehicular Ad hoc Networks (VANETs). Avoiding broadcast storm is one of the considerable challenges in the development of an effective dissemination scheme for VANETs, which leads to extensive rebroadcasting. Reliable emergency messages delivery is another substantial measure of performance, especially in dense traffic and high mobility scenarios. A generic solution to deal with these problems is to cluster vehicles, so that emergency messages can be re-broadcasted to adjacent clusters only by a smaller number of vehicles. Thus, reliable selections of cluster head and relay nodes are important to reduce the number of retransmissions. In this regard, we propose a clustering technique for Reduced Broadcast Overhead Scheme for Emergency Message Dissemination (RBO-EM). RBO-EM is based on the mobility metrics to strengthen the cluster formation, avoid communication overhead and maintain the message reliability in a high mobility scenario. Moreover, we introduce relay nodes based on estimated link stability to limit the number of retransmissions. RBO-EM is evaluated against eminent schemes by varying traffic densities and speed. Simulation results indicate that RBO-EM enables a reasonable performance gain in terms of coverage, end-to-end delay and message reliability.

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Reliable and infrastructure‐independent routing for the internet of vehicles

Taj

Bakhshi

Zandhessami

2023

Int J Communication

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The Internet of Vehicles (IoV) is a new framework for intelligent transportation systems. One of its goals is to improve safety and increase the quality of service for passengers. Topology changes in IoV present significant challenges to the function of safety applications. Most routing algorithms offer their solution, independent of infrastructure or based exclusively on infrastructure. Although the lack of access to roadside units disrupts infrastructure-based algorithms, methods that do not use infrastructure will also not enjoy the benefits of high-speed data transmission. This research proposes the reliable and infrastructure-independent routing (RIIR) routing algorithm to increase the reliability of real-time routing in the IoV. The RIIR, in addition to simultaneous covering capability to use intelligent infrastructure for accelerating data transmission and flexibility in conditions of lack of access to infrastructure, by introducing three new criteria entitled "history of vehicle movement," "conformity of vehicle speed with the harmonic speed average of nearby vehicles," and "number of reliable neighbors," scores vehicles and then selects the most suitable vehicles as route members. The RIIR measures the conformity of the previous presence of vehicles on the current route and the stability of their link with adjacent vehicles. Furthermore, it prevents congestion by halting the spread of route request messages at intersections not leading to the destination. The efficiency of the RIIR has been theoretically proven, and extensive simulations with multiple scenarios in SUMO and NS3 show the superiority of the RIIR in increasing the packet delivery rate and reducing route failure, average delay, and control overhead.

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MCA-V2I: A Multi-hop Clustering Approach over Vehicle-to-Internet communication for improving VANETs performances

Cited by 72 publications

References 18 publications

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

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

RBO-EM: Reduced Broadcast Overhead Scheme for Emergency Message Dissemination in VANETs

Reliable and infrastructure‐independent routing for the internet of vehicles

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