Efficient dissemination based on passive approach and dynamic clustering for VANET

Touil, Abdelali; Ghadi, Fattehallah

doi:10.1016/j.procs.2018.01.134

Cited by 21 publications

(9 citation statements)

References 7 publications

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“…However, the number of clusters constructed and network stability established by CAMONET has still a room of possible improvement. Then, a clustering scheme‐based on the passive data dissemination was proposed by Touil and Ghadi 23 for guaranteeing optimized network stability that prevents network performance degradation. This clustering scheme initiated the cooperating vehicle to send periodical beacon messages based on the information such as position, vehicular speed, and the signal range within the same cluster shared between the vehicular nodes of the network.…”

Section: Related Workmentioning

confidence: 99%

Border Collie optimization algorithm‐based node clustering technique in vehicular ad hoc networks

Godi¹,

Janakiraman²

2022

Trans Emerging Tel Tech

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In vehicular ad hoc networks (VANETs), the nodes are vehicles and these vehicles communicate with one another on the road. The vehicular nodes on the road move continuously and it introduces dynamic changes in the topology of the network. When the node density in the vehicular network is high, then it is still more challenging as these situations introduce different challenges for network scalability and hurdles the process of determining an optimal route in the vehicular network. At this juncture, clustering protocols are often utilized for resolving the issue of network scalability and the factors that hinders process of identifying optimal routes in vehicular network. In this article, Border Collie optimization algorithm‐based node clustering technique (BCOA‐NCT) is proposed for achieving optimal cluster head selection that minimizes network overhead in uncertain node density situations. This BCOA‐NCT is proposed for facilitating equal concentration on both exploitation and exploration during the process of clustering. It utilized the strategy of eyeing for preventing the algorithm from being stuck into local optima during the cluster head selection process. The simulation experiments of the proposed BCOA‐NCT and the benchmarked schemes confirmed better throughput of 6.19%, minimized end‐to‐end delay of 7.24%, reduced mean energy consumptions of 6.89%, and reduction in the number of beacon messages utilized by 8.26% under the impact of different density of vehicular node. The outcome of the results indicated that the proposed BCOA‐NCT on par with the baseline approaches is capable enough in handling the issue of scalability and better estimation of optimal routes under the increase of node density in the vehicular network.

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Section: Related Workmentioning

confidence: 99%

Border Collie optimization algorithm‐based node clustering technique in vehicular ad hoc networks

Godi¹,

Janakiraman²

2022

Trans Emerging Tel Tech

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“…Creating a stable cluster is the main goal of a distributed system-based passive data dissemination technique [38] that can overcome the VANET's communication delay. The message is efficiently transmitted using the passive cluster formation approach.…”

Section: Single-hop Clustering Algorithmmentioning

confidence: 99%

“…The overhead delay and cluster stability problems have been solved using the passive approach in [38], also, the message is transmitted efficiently using this approach.…”

Section: Clustering Algorithms Comparisonmentioning

confidence: 99%

Clustering Review in Vehicular Ad hoc Networks: Algorithms, Comparisons, Challenges and Solutions

Jabbar¹,

Trabelsi

2022

Int. J. Interact. Mob. Technol.

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The Vehicular Ad-hoc Network (VANET) represents a new future for dynamic information dissemination between societies. VANET has a wide range of applications in a variety of aspects, including Intelligent Transportation Systems (ITS). VANET has some characteristics, like highly dynamic topology and intermittent connections. These characteristics lead to untrustworthy information transmission in VANET. Vehicle clustering is an efficient approach to improve the scalability of the network and connection reliability. The performance of the clustering is also affected by VANET characteristics. This article provides a comprehensive description of VANET clustering algorithms. The most notable clustering algorithms introduced between 1999 and 2021 are reviewed. A complete survey on clustering in VANETs is provided based upon the clustering process. The clustering process in most algorithms is explored in the aspects of CH selection metrics, cluster formation, and cluster maintenance. The clustering techniques based on some parameters like stability, convergence, overhead, and latency are compared. Some of the most common problems, as well as the approaches employed to solve them, are also discussed. Also, the performance parameters which evaluate the clustering approaches are summarized.

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“…Another clustering algorithm, named Passive-DCS [60], is proposed for VANET that uses the passive data distribution approach to implement distributed systems. Initially, the proposed approach executes the formation of a cluster by determining neighboring nodes.…”

Section: E Passive-dcsmentioning

confidence: 99%

StabTrust—A Stable and Centralized Trust-Based Clustering Mechanism for IoT Enabled Vehicular Ad-Hoc Networks

et al. 2020

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Vehicular Ad-hoc Network (VANET) is a modern era of dynamic information distribution among societies. VANET provides an extensive diversity of applications in various domains, such as Intelligent Transport System (ITS) and other road safety applications. VANET supports direct communications between vehicles and infrastructure. These direct communications cause bandwidth problems, high power consumption, and other similar issues. To overcome these challenges, clustering methods have been proposed to limit the communication of vehicles with the infrastructure. In clustering, vehicles are grouped together to formulate a cluster based on certain rules. Every cluster consists of a limited number of vehicles/nodes and a cluster head (CH). However, the significant challenge for clustering is to preserve the stability of clusters. Furthermore, a secure mechanism is required to recognize malicious and compromised nodes to overcome the risk of invalid information sharing. In the proposed approach, we address these challenges using components of trust. A trust-based clustering mechanism allows clusters to determine a trustworthy CH. The novel features incorporated in the proposed algorithm includes trust-based CH selection that comprises of knowledge, reputation, and experience of a node. Also, a backup head is determined by analyzing the trust of every node in a cluster. The major significance of using trust in clustering is the identification of malicious and compromised nodes. The recognition of these nodes helps to eliminate the risk of invalid information. We have also evaluated the proposed mechanism with the existing approaches and the results illustrate that the mechanism is able to provide security and improve the stability by increasing the lifetime of CHs and by decreasing the computation overhead of the CH re-selection. The StabTrust also successfully identifies malicious and compromised vehicles and provides robust security against several potential attacks. INDEX TERMS Intelligent transport system, security, vehicular ad-hoc networks, trust-based clustering, VANET attacks.

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Efficient dissemination based on passive approach and dynamic clustering for VANET

Cited by 21 publications

References 7 publications

Border Collie optimization algorithm‐based node clustering technique in vehicular ad hoc networks

Border Collie optimization algorithm‐based node clustering technique in vehicular ad hoc networks

Clustering Review in Vehicular Ad hoc Networks: Algorithms, Comparisons, Challenges and Solutions

StabTrust—A Stable and Centralized Trust-Based Clustering Mechanism for IoT Enabled Vehicular Ad-Hoc Networks

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