VORTEX: Descarregamento de Dados Sensível à Latência ao Longo do Contínuo Edge–Cloud para Veículos Autônomos Conectados

• Mariese C. A. dos Santos UFBA
• João P. M. Fernandes UFBA
• Thiago L. M. Mello UFBA
• António Grilo Universidade de Lisboa
• Maycon L. M. Peixoto UFBA

DOI: https://doi.org/10.5753/sbrc.2026.19757

Resumo

Veículos Autônomos Conectados (CAVs - Connected Autonomous Vehicles) geram fluxos massivos de dados sensoriais que precisam ser processados sob rigorosas restrições de latência, frequentemente excedendo as capacidades computacionais e de armazenamento embarcadas. Este artigo apresenta o VORTEX, um framework de descarregamento em nível de objeto que prioriza objetos detectados em vez de fluxos de vídeo brutos para melhorar o cumprimento dos prazos e a eficiência do uso de largura de banda ao longo do contínuo edge–cloud em redes veiculares heterogêneas LTE/5G. O VORTEX emprega uma heurística distribuída e sensível a prazos que orquestra o posicionamento dos objetos ao longo do contínuo, explorando dinamicamente a proximidade da borda e a elasticidade da nuvem quando os prazos se tornam inviáveis. Os resultados mostram que o VORTEX alcança 99,1% de cumprimento de prazos, reduz o encaminhamento para a nuvem e apresenta melhorias de latência estatisticamente significativas em comparação com os algoritmos de referência EDF, LLF e SDF.

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