Software defined networks: challenges for SDN as an infrastructure for intelligent transport systems based on vehicular networks (2020)
- Autor:
- Autor USP: MENEGUETTE, RODOLFO IPOLITO - ICMC
- Unidade: ICMC
- DOI: 10.1109/DCOSS49796.2020.00042
- Subjects: SISTEMAS DE TRANSPORTES; ARQUITETURA DE SOFTWARE; VEÍCULOS
- Keywords: Software Defined Networks; SDN; Vehicular Network; Intelligent Transport Systems
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Los Alamitos
- Date published: 2020
- Source:
- Título: Proceedings
- ISSN: 2325-2944
- Conference titles: International Conference on Distributed Computing in Sensor Systems - DCOSS
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
MENEGUETTE, Rodolfo Ipolito. Software defined networks: challenges for SDN as an infrastructure for intelligent transport systems based on vehicular networks. 2020, Anais.. Los Alamitos: IEEE, 2020. Disponível em: https://doi.org/10.1109/DCOSS49796.2020.00042. Acesso em: 17 jan. 2026. -
APA
Meneguette, R. I. (2020). Software defined networks: challenges for SDN as an infrastructure for intelligent transport systems based on vehicular networks. In Proceedings. Los Alamitos: IEEE. doi:10.1109/DCOSS49796.2020.00042 -
NLM
Meneguette RI. Software defined networks: challenges for SDN as an infrastructure for intelligent transport systems based on vehicular networks [Internet]. Proceedings. 2020 ;[citado 2026 jan. 17 ] Available from: https://doi.org/10.1109/DCOSS49796.2020.00042 -
Vancouver
Meneguette RI. Software defined networks: challenges for SDN as an infrastructure for intelligent transport systems based on vehicular networks [Internet]. Proceedings. 2020 ;[citado 2026 jan. 17 ] Available from: https://doi.org/10.1109/DCOSS49796.2020.00042 - Resource allocation technique for edge computing using Grey Wolf optimization algorithm
- A framework to develop a cost-effective charging policy for electric vehicles
- Alocação de tarefas em nuvens veiculares utilizando jogos de mercado
- HARMONIC: Shapley values in market games for resource allocation in vehicular clouds
- Machine learning for detection of distributed Denial-of-Service attacks from queries executed in DBMS
- Predicting bull and bear markets: a deep learning and linear regression study in cryptocurrencies
- Lightweight malware classification with FORTUNATE: precision meets computational efficiency
- Predictive congestion control based on collaborative information sharing for vehicular ad hoc networks
- Strategies for locating electric vehicle charging stations in smart cities
- FORTUNATE: Decrypting and classifying malware by variable length instruction sequences
Informações sobre o DOI: 10.1109/DCOSS49796.2020.00042 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3007602.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
