Apresentando e demonstrando novo algoritmo para a melhor alocação de recursos na computação em nuvem com base na filtragem de Kalman
Palavras-chave:
Cloud Computing, Filtro de Kalman, Alocação de Recursos.Resumo
Nas últimas décadas, muita atenção atraiu a computação em nuvem, e isso é apenas por causa dos serviços e poderes apresentados pelos provedores de nuvem. Apresentam diferentes tipos de serviços, tais como: capacidade de processamento, capacidade de armazenamento, Plataforma como Serviço, Software como Serviço. De acordo com especialistas e gerentes de diferentes opiniões do setor, duas principais dificuldades na frente de organizações e empresas para migrar para a computação em nuvem são a segurança e os recursos acessíveis. Neste artigo, queremos introduzir um novo algoritmo de alocação para recursos da nuvem. Esse algoritmo é um algoritmo inteligente, que é baseado na filtragem de Kalman e aloca recursos e poderes aos usuários com base em seus históricos de uso e demanda atual.
Downloads
Não há dados estatísticos.
Referências
Bruce, Berriman, G., Deelman, E., Groth, P., Juve G. (2011). The application of cloud computing to the creation of image mosaics and management of their provenance.
Buyya, R., Yeo, C.S., Venugopal, S., Broberg J., Brandic, I. (2012). cloud computing and Emerging IT platforms: Vision, Hype, and Reality for delivering computing as the 5th utility.
Campbell, R., Gupta, I., Heath, M., Ko, S.Y., Kozuch, M., Kunze, M., Kwan, T., Lai, K., Lee, H.Y., Lyons, M., Milojicic, D., O’Hallaron, D., Soh, Y.C. (2013). open cirrus TM cloud computing testbed: federated data centers for open source systems and services research,
Chard K., Caton, S., Rana, O., Bubendorfer, K. (2008). social cloud: cloud computing in social networks.
Cryans, J.D., April, A., Abran, A. (2008). criteria to compare cloud computing with current database technology, R. Dumke et al. (Eds.): IWSM / MetriKon / Mensura 2008, LNCS 5338, pp. 114-126.
Darbandi, M. (2017). Kalman Filtering for Estimation and Prediction Servers with Lower Traffic Loads for Transferring High-Level Processes in Cloud Computing; Published by HCTL International Journal of Technology Innovations and Research, (ISSN: 2321-1814), Vol. 23, Issue 1, pp. 10-20, Feb. DOI: 10.5281/Zenodo.345288.
Darbandi, M. (2017a). Proposing New Intelligence Algorithm for Suggesting Better Services to Cloud Users based on Kalman Filtering”; Published by Journal of Computer Sciences and Applications, Vol. 5, Issue 1, PP. 11-16.
Darbandi, M. (2017b). Proposing New Intelligent System for Suggesting Better Service Providers in Cloud Computing based on Kalman Filtering.
Published by HCTL International Journal of Technology Innovations and Research, Vol. 24, Issue 1, pp. 1-9.
Darbandi, M., Yousefi, S. (2017). Feasibility Study and Designing Smart Software for Control and Assessment of Human Health by means of Cloud Computing and Kalman Filtering [In Persian]; Published by International Journal of Researches in Science and Engineering, pp. 1-14.
Farahani Rad, A. (2013). Cloud Computing and its Implications for Organizational Design and Performance, MSC. Thesis, MIT University, USA.
Francis, L. (2009). Cloud Computing: Implications for Enterprise Software Vendors, MSC. Thesis, MIT University, USA.
Kashefi, F., Darbandi, M. (2011). Perusal about influences of Cloud Computing on the processes of these days and presenting new ideas about its security, International IEEE Conf. AICT., Dec. Baku,Azerbaijan.
Lundblad, J.J. (1974). Application of the Extended Kalman Filtering Technique to Ship Maneuvering Analysis, MSC. Thesis, MIT University, USA.
Madhavapeddy, A., Mortier, R., Crowcroft, J., Hand S. (2010). Multiscale not multi core: efficient heterogeneous cloud computing, published by the British Informatics Society Ltd. Proceedings of ACM-BCS Visions of Computer Science.
Menasce D.A., Ngo P. (2009). understanding cloud computing: experimentation and capacity planning. Proc. 2009, Computer Measurement Group Conf. Dallas, TX. Dec.
Buyya, R., Yeo, C.S., Venugopal, S., Broberg J., Brandic, I. (2012). cloud computing and Emerging IT platforms: Vision, Hype, and Reality for delivering computing as the 5th utility.
Campbell, R., Gupta, I., Heath, M., Ko, S.Y., Kozuch, M., Kunze, M., Kwan, T., Lai, K., Lee, H.Y., Lyons, M., Milojicic, D., O’Hallaron, D., Soh, Y.C. (2013). open cirrus TM cloud computing testbed: federated data centers for open source systems and services research,
Chard K., Caton, S., Rana, O., Bubendorfer, K. (2008). social cloud: cloud computing in social networks.
Cryans, J.D., April, A., Abran, A. (2008). criteria to compare cloud computing with current database technology, R. Dumke et al. (Eds.): IWSM / MetriKon / Mensura 2008, LNCS 5338, pp. 114-126.
Darbandi, M. (2017). Kalman Filtering for Estimation and Prediction Servers with Lower Traffic Loads for Transferring High-Level Processes in Cloud Computing; Published by HCTL International Journal of Technology Innovations and Research, (ISSN: 2321-1814), Vol. 23, Issue 1, pp. 10-20, Feb. DOI: 10.5281/Zenodo.345288.
Darbandi, M. (2017a). Proposing New Intelligence Algorithm for Suggesting Better Services to Cloud Users based on Kalman Filtering”; Published by Journal of Computer Sciences and Applications, Vol. 5, Issue 1, PP. 11-16.
Darbandi, M. (2017b). Proposing New Intelligent System for Suggesting Better Service Providers in Cloud Computing based on Kalman Filtering.
Published by HCTL International Journal of Technology Innovations and Research, Vol. 24, Issue 1, pp. 1-9.
Darbandi, M., Yousefi, S. (2017). Feasibility Study and Designing Smart Software for Control and Assessment of Human Health by means of Cloud Computing and Kalman Filtering [In Persian]; Published by International Journal of Researches in Science and Engineering, pp. 1-14.
Farahani Rad, A. (2013). Cloud Computing and its Implications for Organizational Design and Performance, MSC. Thesis, MIT University, USA.
Francis, L. (2009). Cloud Computing: Implications for Enterprise Software Vendors, MSC. Thesis, MIT University, USA.
Kashefi, F., Darbandi, M. (2011). Perusal about influences of Cloud Computing on the processes of these days and presenting new ideas about its security, International IEEE Conf. AICT., Dec. Baku,Azerbaijan.
Lundblad, J.J. (1974). Application of the Extended Kalman Filtering Technique to Ship Maneuvering Analysis, MSC. Thesis, MIT University, USA.
Madhavapeddy, A., Mortier, R., Crowcroft, J., Hand S. (2010). Multiscale not multi core: efficient heterogeneous cloud computing, published by the British Informatics Society Ltd. Proceedings of ACM-BCS Visions of Computer Science.
Menasce D.A., Ngo P. (2009). understanding cloud computing: experimentation and capacity planning. Proc. 2009, Computer Measurement Group Conf. Dallas, TX. Dec.
Downloads
Publicado
2018-12-27
Como Citar
Khosravi, S. (2018). Apresentando e demonstrando novo algoritmo para a melhor alocação de recursos na computação em nuvem com base na filtragem de Kalman. Amazonia Investiga, 7(17), 200–210. Recuperado de https://amazoniainvestiga.info/index.php/amazonia/article/view/344
Edição
Seção
Articles
.gif)
