Resource Allocation in Vehicular Clouds Based on Game Theory

• Aguimar R. Júnior USP
• Rodolfo I. Meneguette USP

DOI: https://doi.org/10.5753/sbrc_estendido.2024.1615

Abstract

Resource allocation in vehicular networks (RAVN) faces increasing challenges as the number of connected vehicles grows, requiring solutions that effectively deal with high mobility and diversity of nodes. In this context, Game Theory (GT) is a valuable approach, offering a mathematical framework for the analysis of strategic decisions. This work presents HARMONIC, a heuristic solution that uses GT to model the RAVN problem. The solution also utilizes the concept of Shapley Values to optimize the task allocation order and distribute these tasks among a larger number of vehicular clouds. The results obtained through simulations show a reduction in the number of cycles needed for allocation and lower failure rates, compared to other solutions discussed in the literature.

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