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Improving the quality of real-time data transmission service in VANETS by balancing the load on road side units.

Authors :
Saemi, Behzad
Halataei, Fatemeh
Ahmadi, Rouhollah
Ashkaran, Ali
Mirkamali, SeyedSaeid
Hosseinabadi, Ali Asghar Rahmani
Source :
Cluster Computing. Aug2024, Vol. 27 Issue 5, p6471-6487. 17p.
Publication Year :
2024

Abstract

Vehicular Ad Hoc Networks (VANETs) play a critical role in ensuring safety and welfare applications for drivers and passengers amidst the escalating vehicular population in urban environments. The efficient functioning of VANETs hinges on addressing the challenge of load balancing among Road Side Units (RSUs). This paper introduces a groundbreaking approach aimed at enhancing real-time data transmission services within VANETs. The key contribution lies in the development of a multicast routing algorithm utilizing a geo-targeting protocol, facilitating simultaneous delivery of source data packets to multiple destinations. This innovative strategy aims to alleviate RSU congestion, thereby significantly enhancing the quality of real-time data transmission services. Moreover, this study presents advancements in the Statistical Match and Queuing algorithm, refining it over time to substantially mitigate network congestion and redundancy. Additionally, a Multi-Protocol Label Switching based algorithm is implemented to elevate service quality parameters, including end-to-end latency, packet loss, and overall network efficiency within in-vehicle networks. Importantly, this approach remains adaptable across various Layer two technologies, ensuring compatibility and scalability. Simulation results validate the efficacy of the proposed methodology, showcasing its superiority over existing methods. The findings underscore the innovative algorithms' prowess in addressing load balancing challenges across diverse scenarios, affirming their potential to significantly enhance VANET service quality. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13867857
Volume :
27
Issue :
5
Database :
Academic Search Index
Journal :
Cluster Computing
Publication Type :
Academic Journal
Accession number :
178969943
Full Text :
https://doi.org/10.1007/s10586-024-04317-6