Network Congestion Visualization for Vehicular Communication using Streamlit Approach

Abstract

In the modern realm of Mobile Communication with various velocities of mobility, vehicular networks play a vital role in ensuring seamless communication without loss in the network connection. However, the efficacy and reliability of these networks are significantly impacted by ubiquitous network congestion. Understanding the dynamics of network congestion is essential for optimizing the intricate complexities inherent in vehicular systems. This research undertakes a comparative analysis of two distinct methods for visualizing network congestion within vehicular networks. The first approach utilizes Streamlit, a Python library, while the second employs MATLAB based for visualization. Through detailed implementation and evaluation, this study elucidates the strengths, limitations, and advantages of each method. Such insights are invaluable for practitioners and researchers specializing in vehicle networking and associated visualizations, offering a comprehensive understanding of the subject matter. This research developed the algorithms for verification of congestion in the vehicular network, the same has been cross verified with two methods.