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