Cluster Formation and Cluster Head Selection Approach for Vehicle Ad-Hoc Network (VANETs) using K-Means and Floyd-Warshall Technique

Hussain, Iftikhar; Chen, Bingcai

doi:10.14569/ijacsa.2017.081202

Cited by 30 publications

(17 citation statements)

References 17 publications

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“…cluster-member(VNDN) 3. if ðTRUEÞ then cluster-member() ⟵ Cn V PID ⟵ allocate((V pk , V prk )) else !cluster-member() Wireless Communications and Mobile Computing cluster head-based minor node selection with push-based and on-demand content placement strategies in the VNDN environment [30]. The SVC-caching strategy provides complete V2V communications in the NDN environment.…”

Section: Proposed Methodologymentioning

confidence: 99%

Named Data Networking‐Based On‐Demand Secure Vehicle‐To‐Vehicle Communications

Saleem

Din

Almogren

et al. 2021

Wireless Communications and Mobile Computing

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The detection of secure vehicles for content placement in vehicle to vehicle (V2V) communications makes a challenging situation for a well-organized dynamic nature of vehicular ad hoc networks (VANET). With the increase in the demand of efficient and adoptable content delivery, information-centric networking (ICN) can be a promising solution for the future needs of the network. ICN provides a direct retrieval of content through its unique name, which is independent of locations. It also performs better in content retrieval with its in-network caching and named-based routing capabilities. Since vehicles are mobile devices, it is very crucial to select a caching node, which is secure and reliable. The security of data is quite important in the vehicular named data networking (VNDN) environment due to its vital importance in saving the life of drivers and pedestrians. To overcome the issue of security and reduce network load in addition to detect a malicious activity, we define a blockchain-based distributive trust model to achieve security, trust, and privacy of the communicating entities in VNDN, named secure vehicle communication caching (SVC-caching) mechanism for the placement of on-demand data. The proposed trust management mechanism is decentralized in nature, which is used to select a trustworthy node for cluster-based V2V communications in the VNDN environment. The SVC-caching strategy is simulated in the NS-2 simulator. The results are evaluated based on one-hop count, delivery ratio, cache hit ratio, and malicious node detection. The results demonstrate that the proposed technique improves the performance based on the selected parameters.

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Section: Proposed Methodologymentioning

confidence: 99%

Named Data Networking‐Based On‐Demand Secure Vehicle‐To‐Vehicle Communications

Saleem

Din

Almogren

et al. 2021

Wireless Communications and Mobile Computing

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“…This literature survey focuses more on VANETs clustering. Some approaches of VANETs clustering uses statistical clustering such as K-means [23], or other models that apply density metrics in clustering. In the work of [24], an approach for clustering based on density metric is proposed.…”

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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“…The centralized vehicle was selected as the cluster head in case of Floyd-Warshall algorithm. The stability time was improved during the selection of cluster head through proposed method [33]. A combination of bulley and Lamport timestamp algorithm was presented for the cluster head selection in [34].…”

Section: Related Work and Backgroundmentioning

confidence: 99%

Expansion of Cluster Head Stability Using Fuzzy in Cognitive Radio CR-VANET

et al. 2019

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The Vehicular Ad Hoc Network (VANET) plays a vital role in the development of smart cities, especially in ensuring vehicles' safety on roads. However, VANET wireless-based networks face some challenges such as security, stability, communication, and reliability. To resolve these issues, we propose a fuzzy cluster head selection scheme in Cognitive Radio (CR) VANET, which uses the CR technology for the spectrum sensing algorithm. In this technology, the free spectrums of the primary user are utilized by secondary users without any correlation. Moreover, we have considered some input parameters such as vehicles' average velocity, distance, network connectivity level, lane weight and trustworthiness for the fuzzy system based CR VANET in this research. The selected cluster head provides stability and reliability to the cluster compared to the state of art techniques. Extensive experiments were conducted in order to evaluate the effectiveness of the proposed approach. However, simulation results authenticate more stable and secure cluster formation using the proposed fuzzy logic based CR VANET.

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Cluster Formation and Cluster Head Selection Approach for Vehicle Ad-Hoc Network (VANETs) using K-Means and Floyd-Warshall Technique

Cited by 30 publications

References 17 publications

Named Data Networking‐Based On‐Demand Secure Vehicle‐To‐Vehicle Communications

Named Data Networking‐Based On‐Demand Secure Vehicle‐To‐Vehicle Communications

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

Expansion of Cluster Head Stability Using Fuzzy in Cognitive Radio CR-VANET

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