SARSA RL for edge connectivity management in vehicular edge networks (2024)
- Authors:
- Autor USP: MENEGUETTE, RODOLFO IPOLITO - ICMC
- Unidade: ICMC
- DOI: 10.1109/CloudNet62863.2024.10815889
- Subjects: SISTEMAS INTELIGENTES DE TRANSPORTES; REDES AD HOC VEICULARES; ALGORITMOS
- Keywords: Edge; SARSA; Data and Resource Sharing; High Mobility; Ultra-dense Network
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2024
- Source:
- Título: Proceedings
- ISSN: 2689-7563
- Conference titles: International Conference on Cloud Networking - CloudNet
- Status:
- Nenhuma versão em acesso aberto identificada
-
ABNT
FERDOUS, Jannatul et al. SARSA RL for edge connectivity management in vehicular edge networks. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/CloudNet62863.2024.10815889. Acesso em: 06 maio 2026. -
APA
Ferdous, J., Murshed, M., Meneguette, R. I., & Grande, R. E. de. (2024). SARSA RL for edge connectivity management in vehicular edge networks. In Proceedings. Piscataway: IEEE. doi:10.1109/CloudNet62863.2024.10815889 -
NLM
Ferdous J, Murshed M, Meneguette RI, Grande RE de. SARSA RL for edge connectivity management in vehicular edge networks [Internet]. Proceedings. 2024 ;[citado 2026 maio 06 ] Available from: https://doi.org/10.1109/CloudNet62863.2024.10815889 -
Vancouver
Ferdous J, Murshed M, Meneguette RI, Grande RE de. SARSA RL for edge connectivity management in vehicular edge networks [Internet]. Proceedings. 2024 ;[citado 2026 maio 06 ] Available from: https://doi.org/10.1109/CloudNet62863.2024.10815889 - Modelo de um corredor para mobilidade urbana de aeronaves não tripuladas no "eixão" de Brasília
- A computational intelligence-driven reference architecture for anomaly detection in software-defined networking (SDN)
- Adaptive bat-inspired Optimization for infrastructure-agnostic task allocation in vehicular fogs
- FedIHRAS: a privacy-preserving federated learning framework for multi-institutional collaborative radiological analysis with integrated explainability and automated clinical reporting
- FORTUNATE: Decrypting and classifying malware by variable length instruction sequences
- Predicting bull and bear markets: a deep learning and linear regression study in cryptocurrencies
- ONSPRIDE: an ontology-based framework for privacy by design in distributed networks apps
- Optimized solutions for deploying a militarized 4G/LTE network with maximum coverage and minimum interference
- Lightweight malware classification with FORTUNATE: precision meets computational efficiency
- ELINAC: autoencoder approach for electronic invoices data clustering
Informações sobre a disponibilidade de versões do artigo em acesso aberto coletadas automaticamente via oaDOI API (Unpaywall).
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3231445.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
