Aplicando Análise Consensual Fuzzy para Tomada de Decisão na Alocação de Recursos em Nuvem Computacionais
Resumo
Este artigo contempla a concepção de uma abordagem que explora medidas de consenso fuzzy, como suporte a problemas de tomada de decisão relacionados à determinação do nível de utilização das máquinas físicas em um ambiente de computação em nuvem. A análise de consenso dos conjuntos fuzzy está baseada nas médias aritméticas e exponenciais. Para avaliar a proposta foi concebido um estudo de caso direcionado a arquitetura do Framework Int-FLBCC em desenvolvimento pelo grupo de pesquisa.
Palavras-chave:
Lógica Fuzzy Valorada Intervalarmente, Computação em Nuvem, Computação Verde, Análise de Consenso
Referências
Beliakov, G., Calvo, T., and James, S. (2014). Consensus measures constructed from aggregation functions and fuzzy implications. Knowl.-Based Syst., 55:1–8.
Elkano, M., Galar, M., Sanz, J. A., Schiavo, P. F., Pereira Jr, S., Dimuro, G. P., Borges, E. N., and Bustince, H. (2018). Consensus via penalty functions for decision making in ensembles in fuzzy rule-based classification systems. Appl. Soft Comput., 67:728–740.
Gehrke, M., Walker, C., and Walker, E. (1996). Some comments on interval valued fuzzy sets. Int. Journal of Intelligent Systems, 11(10):751–759.
Gourisaria, M. K., Samanta, A., Saha, A., Patra, S. S., and Khilar, P. M. (2020). An extensive review on cloud computing. In Data Engineering and Communication Technology, pages 53–78.
Karnik, N. N. and Mendel, J. M. (1998). Introduction to type-2 fuzzy logic systems. In 1998 IEEE Int. Conf. on Fuzzy Systems Proc.., volume 2, pages 915–920 vol.2.
Klement, E., Mesiar, R., and Pap, E. (2004). Triangular norms. position paper I: basic analytical and algebraic properties. Fuzzy Sets and Systems, 143(1):5–26.
Mendel, J., Hagras, H., Tan, W.-W., Melek, W. W., and Ying, H. (2014). Introduction to type-2 fuzzy logic control: theory and applications. John Wiley & Sons.
Mendel, J. M. (2003). Fuzzy sets for words: a new beginning. In Fuzzy Systems, 2003. FUZZ ’03. The 12th IEEE Int. Conf. on, volume 1, pages 37–42.
Mendel, J. M., John, R. I., and Liu, F. (2006). Interval type-2 fuzzy logic systems made simple. IEEE Trans. Fuzzy Systems, 14(6):808–821.
Moura, B. M., Schneider, G. B., Yamin, A. C., Santos, H., Reiser, R. H., and Bedregal, B. (2021). Interval-valued fuzzy logic approach for overloaded hosts in consolidation of virtual machines in cloud computing. Fuzzy Sets and Systems.
Nathani, A., Chaudhary, S., and Somani, G. (2012). Policy based resource allocation in iaas cloud. Future Generation Computer Systems, 28(1):94–103.
Oliveira, L., De Moura, R. C., Schneider, G. B., Pilla, M. L., Yamin, A. C., Reiser, R. H. S., and Bedregal, B. R. C. (2021). Toward a fuzzy logic-based consensus analysis in hybrid memory management. In 2021 IEEE Int. Conf. on Fuzzy Systems (FUZZIEEE), pages 1–6.
Shehabi, A., Smith, S., Sartor, D., Brown, R., Herrlin, M., Koomey, J., Masanet, E., Horner, N., Azevedo, I., and Lintner, W. (2016). United states data center energy usage report.
Tsuchiya, Y. and Hiramoto, N. (2018). Measuring consensus and dissensus: A generalized index of disagreement using conditional probability. Inf. Sci., 439-440:50–60.
Wu, D. and Nie, M. (2011). Comparison and practical implementation of type-reduction algorithms for type-2 fuzzy sets and systems. In FUZZ-IEEE, pages 2131–2138. IEEE.
Zhang, Q., Cheng, L., and Boutaba, R. (2010). Cloud computing: state-of-the-art and research challenges. Journal of Internet Services and Applications, 1(1):7–18.
Elkano, M., Galar, M., Sanz, J. A., Schiavo, P. F., Pereira Jr, S., Dimuro, G. P., Borges, E. N., and Bustince, H. (2018). Consensus via penalty functions for decision making in ensembles in fuzzy rule-based classification systems. Appl. Soft Comput., 67:728–740.
Gehrke, M., Walker, C., and Walker, E. (1996). Some comments on interval valued fuzzy sets. Int. Journal of Intelligent Systems, 11(10):751–759.
Gourisaria, M. K., Samanta, A., Saha, A., Patra, S. S., and Khilar, P. M. (2020). An extensive review on cloud computing. In Data Engineering and Communication Technology, pages 53–78.
Karnik, N. N. and Mendel, J. M. (1998). Introduction to type-2 fuzzy logic systems. In 1998 IEEE Int. Conf. on Fuzzy Systems Proc.., volume 2, pages 915–920 vol.2.
Klement, E., Mesiar, R., and Pap, E. (2004). Triangular norms. position paper I: basic analytical and algebraic properties. Fuzzy Sets and Systems, 143(1):5–26.
Mendel, J., Hagras, H., Tan, W.-W., Melek, W. W., and Ying, H. (2014). Introduction to type-2 fuzzy logic control: theory and applications. John Wiley & Sons.
Mendel, J. M. (2003). Fuzzy sets for words: a new beginning. In Fuzzy Systems, 2003. FUZZ ’03. The 12th IEEE Int. Conf. on, volume 1, pages 37–42.
Mendel, J. M., John, R. I., and Liu, F. (2006). Interval type-2 fuzzy logic systems made simple. IEEE Trans. Fuzzy Systems, 14(6):808–821.
Moura, B. M., Schneider, G. B., Yamin, A. C., Santos, H., Reiser, R. H., and Bedregal, B. (2021). Interval-valued fuzzy logic approach for overloaded hosts in consolidation of virtual machines in cloud computing. Fuzzy Sets and Systems.
Nathani, A., Chaudhary, S., and Somani, G. (2012). Policy based resource allocation in iaas cloud. Future Generation Computer Systems, 28(1):94–103.
Oliveira, L., De Moura, R. C., Schneider, G. B., Pilla, M. L., Yamin, A. C., Reiser, R. H. S., and Bedregal, B. R. C. (2021). Toward a fuzzy logic-based consensus analysis in hybrid memory management. In 2021 IEEE Int. Conf. on Fuzzy Systems (FUZZIEEE), pages 1–6.
Shehabi, A., Smith, S., Sartor, D., Brown, R., Herrlin, M., Koomey, J., Masanet, E., Horner, N., Azevedo, I., and Lintner, W. (2016). United states data center energy usage report.
Tsuchiya, Y. and Hiramoto, N. (2018). Measuring consensus and dissensus: A generalized index of disagreement using conditional probability. Inf. Sci., 439-440:50–60.
Wu, D. and Nie, M. (2011). Comparison and practical implementation of type-reduction algorithms for type-2 fuzzy sets and systems. In FUZZ-IEEE, pages 2131–2138. IEEE.
Zhang, Q., Cheng, L., and Boutaba, R. (2010). Cloud computing: state-of-the-art and research challenges. Journal of Internet Services and Applications, 1(1):7–18.
Publicado
17/11/2021
Como Citar
SCHNEIDER, Guilherme; MOURA, Bruno; MONKS, Eduardo; YAMIN, Adenauer; SANTOS, Helida; REISER, Renata.
Aplicando Análise Consensual Fuzzy para Tomada de Decisão na Alocação de Recursos em Nuvem Computacionais. In: WORKSHOP-ESCOLA DE INFORMÁTICA TEÓRICA (WEIT), 6. , 2021, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 41-48.
DOI: https://doi.org/10.5753/weit.2021.18920.
