Abstract
With the growth of Vehicular Ad-hoc Networks, many services delivery is gaining more attention from the intelligent transportation system. However, mobility characteristics of vehicular networks cause frequent disconnection of routes, especially during the delivery of data. In both developed and developing countries, a lot of time is consumed due to traffic congestion. This has significant negative consequences, including driver stress due to increased time demand, decreased productivity for various personalized and commercial vehicles, and increased emissions of hazardous gases especially air polluting gases are impacting public health in highly populated areas. Clustering is one of the most powerful strategies for achieving a consistent topological structure. Two algorithms are presented in this research work. First, a k-means clustering algorithm in which dynamic grouping by k-implies is performed that fits well with Vehicular network’s dynamic topology characteristics. The suggested clustering reduces overhead and traffic management. Second, for inter and intra-clustering routing, the dynamic routing protocol is proposed, which increases the overall Packet Delivery Ratio and decreases the End-to-End latency. Relative to the cluster-based approach, the proposed protocol achieves improved efficiency in terms of Throughput, Packet Delivery Ratio, and End-to-End delay parameters comparing the situations by taking different number of vehicular nodes in the network.
Highlights
IntroductionThe Vehicular Ad hoc Networks (VANETs) are research network that pursues the future of pervasive computing [1]
Relative to the cluster-based approach, the proposed protocol achieves improved efficiency in terms of Throughput, Packet Delivery Ratio, and End-to-End delay parameters comparing the situations by taking different number of vehicular nodes in the network
The Vehicular Ad hoc Networks (VANETs) are research network that pursues the future of pervasive computing [1]
Summary
The Vehicular Ad hoc Networks (VANETs) are research network that pursues the future of pervasive computing [1]. VANETs cluster-based networking system forms a trusted backbone for the efficient transmission of messages and associated reserves all vehicles inside the network [4,5]. In VANETs, clustering routing contributes to decreased network dynamics [6]. We propose a dynamic clustering protocol utilizing k-means for CH selection and cluster forming in this paper, which increases the overall distribution ratio of packets and reduces VANETs end-to-end latency. The clustering of K-means divides the region into four segments, and each segment has several CHs. The objective function is determined using key vehicle parameters, such as position (X, Y), speed, direction and point of interest (POI). The main objective of this paper is to create a clustering protocol that increases packet delivery ratio (PDR) .and decreases the end-to-end (E2E) delay via K-means clustering and dynamic routing.
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