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4 July 2020

15 Pages

Towards Improved Vehicular Information-Centric Networks by Efficient Caching Discovery

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1
Institute of Computing, University of Campinas, Campinas 13083-852, Brazil
2
Digital Metropolis Institute, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil
3
Department of Computer Science, Institute of Exact Sciences, University of Brasília (UnB), Campus Darcy Ribeiro, Asa Norte, Federal District, Brasília-DF 70910-900, Brazil
4
Instituto de Telecomunicações, University of Aveiro, 3810-193 Aveiro, Portugal

Abstract

The number of connected cars and the massive consumption of digital content on the Internet have increased daily. However, the high mobility of the vehicles, coming from patterns’ variation over time, makes efficient large-scale content distribution quite challenging. In light of this, the emerging Vehicular Named Data Network (VNDN) architecture provides support for content-centric network communications and caching capabilities, which allows reliable and larger-scale content delivery over Vehicular Ad-Hoc Networks (VANETs). This notwithstanding, the high number of interest packets in VNDN tends to introduce broadcast storm occurrences during the cache discovery process. Thus, network performance degradation comes up for the influence of both increased packet loss rates and delays on content recovery during communication between vehicles. This work proposes a new cache discOVEry pRoTocol (OVERT VNDN), which combines the computational geometry and degree centrality concepts to tackle the VNDN performance degradation challenges and issues. The main idea behind OVERT VNDN is to choose the most appropriate relay vehicles to engage interest packets’ delivery within the VNDN, seeking to achieve higher network performance by optimizing broadcast storm incidence. The obtained results suggest that OVERT VNDN outperforms its competitor in the following key performance indicators: (i) improving the cache discovery process by 120.47%; (ii) enhancing the content delivery rate by 43%; and (iii) reducing the number of interest packets by 80.99%.

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