The chapter appears to be important for the scientific community, particularly in the field of vehicular communication and smart cities. It addresses a significant challenge related to scalability in vehicular ad hoc networks (VANETs), which is crucial for the effective implementation of smart city technologies. The proposed Eigen trick-based Hypergraph Stable Clustering algorithm (EtHgSC) introduces innovative approaches, such as an improved hypergraph-based spectral clustering algorithm and a two-fold scheme for stable Cluster Head (CH) selection, to enhance the stability and efficiency of VANETs. The inclusion of metrics like vehicle time to leave and the application of the grey relational analysis model demonstrate a comprehensive and novel approach. The reported positive results in terms of CH lifetime, cluster member (CM) lifetime, and packet delay reduction further emphasize the potential significance of this manuscript in advancing the understanding and application of vehicular communication strategies in smart cities.
Author(s) Details:
Mays Kareem Jabbar,
Faculty of Engineering, University of Misan, Al Amarah City, Misan Province, 62001, Iraq and CES_Lab, Ecole National d’Ingénieurs de Sfax (ENIS), Sfax University, Tunisia.
Hafedh Trabelsi,
CES_Lab, Ecole National d’Ingénieurs de Sfax (ENIS), Sfax University, Tunisia.
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