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Enhancing Vehicular Communication Through Neutrosophic Queueing Theory and Network Analysis-Based Traffic Signal Optimization
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Author(s): M. Clement Joe Anand (Mount Carmel College, Bengaluru, India), V. A. Anjana (Mount Carmel College, Bengaluru, India), Manokamana Agarwal (Silver Oak College of Engineering and Technology, Silver Oak University, India), Utpal Saikia (Silapathar College, India), B. Ranjitha (Mohan Babu University, India)and Chitra Ramaprakash (Dayananda Sagar College of Engineering, India)
Copyright: 2025
Pages: 26
Source title:
Networking, Transport, and Quality of Service in Vehicular Networks
Source Author(s)/Editor(s): Truong Khang Nguyen (Van Lang University, Vietnam)and Devasis Pradhan (Acharya Institute of Technology, India)
DOI: 10.4018/979-8-3693-6422-2.ch001
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Abstract
This chapter explores the integration of Neutrosophic Queuing Theory (NQT) and Neutrosophic Network Analysis (NNA) into the realm of vehicular communication at traffic signals to address the uncertainties and complexities of traffic flow, including variable arrival rates, unpredictable service times, and dynamic network conditions. Using real-world traffic data, a neutrosophic queueing model is developed to optimize traffic signal timings specifically for enhancing vehicular communication by determining key traffic parameters such as traffic intensity, the probability of crossing the signal, and various performance measures emphasizing the expected waiting time and queue length. Also proposes a novel framework that integrates NNA into the design and optimization of communication protocols for vehicles at traffic signals with the help of the score function and modified Kruskal's algorithm. The results demonstrate significant improvements in communication reliability, reduced latency, and enhanced system throughput, highlighting the effectiveness of the proposed approach in enhancing vehicular communication efficiency.
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