Thematic series on service composition for the future internet (2016)
- Authors:
- Autor USP: LEJBMAN, ALFREDO GOLDMAN VEL - IME
- Unidade: IME
- DOI: 10.1186/s13174-016-0045-9
- Subjects: INTERNET; CIÊNCIA DA COMPUTAÇÃO
- Language: Inglês
- Imprenta:
- Publisher place: Heidelberg
- Date published: 2016
- Source:
- Título: Journal of Internet Services and Applications
- ISSN: 1869-0238
- Volume/Número/Paginação/Ano: v. 7, n. 1, 4 p., article n.º 3, Dec. 2016
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
AUTILI, Marco e TIVOLI, Massimo e GOLDMAN, Alfredo. Thematic series on service composition for the future internet. Journal of Internet Services and Applications. Heidelberg: Instituto de Matemática e Estatística, Universidade de São Paulo. Disponível em: https://doi.org/10.1186/s13174-016-0045-9. Acesso em: 10 fev. 2026. , 2016 -
APA
Autili, M., Tivoli, M., & Goldman, A. (2016). Thematic series on service composition for the future internet. Journal of Internet Services and Applications. Heidelberg: Instituto de Matemática e Estatística, Universidade de São Paulo. doi:10.1186/s13174-016-0045-9 -
NLM
Autili M, Tivoli M, Goldman A. Thematic series on service composition for the future internet [Internet]. Journal of Internet Services and Applications. 2016 ; 7( article º 3): 4 .[citado 2026 fev. 10 ] Available from: https://doi.org/10.1186/s13174-016-0045-9 -
Vancouver
Autili M, Tivoli M, Goldman A. Thematic series on service composition for the future internet [Internet]. Journal of Internet Services and Applications. 2016 ; 7( article º 3): 4 .[citado 2026 fev. 10 ] Available from: https://doi.org/10.1186/s13174-016-0045-9 - The influence of organizational factors on inter-team knowledge sharing effectiveness in agile environments
- Improving the performance of actor model runtime environments on multicore and manycore platforms
- Towards automatic actor pinning on multi-core architectures
- A simple BSP-based model to predict execution time in GPU applications
- A comparison of GPU execution time prediction using machine learning and analytical modeling
- Message from the program committee co-chairs. [Apresentação]
- Useful statistical methods for human factors research in software engineering: a discussion on validation with quantitative data
- Trying to increase the mature use of agile practices by Group Development Psychology Training: an experiment
- Scheduling moldable BSP tasks on clouds
- A multithreaded resolution of the service selection problem based on domain decomposition and work stealing
Informações sobre o DOI: 10.1186/s13174-016-0045-9 (Fonte: oaDOI API)
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
