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January 1, 2026International Journal of Heavy Vehicle Systems

FraSNA-Net: traffic aware content caching vehicular social networks using fractional shuffle neuron attention network

Vedha Vinodha Doraiswamy Malathy Subramanium

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Key Points

The aim is to improve content caching strategies in vehicular social networks by employing traffic awareness techniques using a fractional shuffle neuron attention network.
Developed a novel fractional shuffle neuron attention network for content caching.
Implemented simulations in a vehicular social network environment to assess performance improvements.
Analyzed caching efficiency against traditional methods.
Enhanced content delivery speed by 30% compared to standard methods.
Reduced network congestion significantly during peak traffic hours.
Achieved a 25% higher cache hit rate, improving user experience.

Implication

Evaluates traffic aware content caching in vehicular networks, suggesting improved efficiency.

Abstract

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Cite This Study

Doraiswamy et al. (2026) studied this question.

synapsesocial.com/papers/6a168b160c924ddd1bd59f2f https://doi.org/10.1504/ijhvs.2026.10078757

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