Open Access

ARTICLE

Implementation of K-Means Algorithm and Dynamic Routing Protocol in VANET

Manoj Sindhwani¹, Charanjeet Singh^1,*, Rajeshwar Singh²

1 School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, 144411, India
2 Doaba Group of Colleges, Nawanshar, 144517, India

* Corresponding Author: Charanjeet Singh. Email:

(This article belongs to the Special Issue: Emerging Trends in Intelligent Communication and Wireless Technologies)

Computer Systems Science and Engineering 2022, 40(2), 455-467. https://doi.org/10.32604/csse.2022.018498

Received 10 March 2021; Accepted 01 May 2021; Issue published 09 September 2021

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.

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Keywords

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