Abstract
The advance of technologies such as distributed computing, Internet and grid computing, have enabled Cloud Computing to become part of a new model of computing and business. Cloud Computing is transforming the traditional ways in which companies use and acquire Information Technology (IT) resources. After an initial boom in Public Cloud, companies begun to mount hybrid Clouds that offer the advantages of Cloud Computing in addition to the privacy of data they consider strategic. A hybrid Cloud solution allows the integration of both systems. Leading companies in cloud solutions have understood this evolution and begun to offer hybrid solutions. Moreover, many of these companies are taking the next step by offering solutions based on open source standards that allow a high degree of interoperability and portability.
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References
Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., Ghalsas, A.: Cloud computing—the business perspective. Decis. Support Syst. 51(1), 176–189 (2011)
Armbrust, M., et al.: A view of cloud computing: Commun. ACM 53(4), 50–58 (2010)
Mell, P., Grance, T.: The NIST definition of cloud computing. NIST Special Publication 800–145, Gaithersburg (2011)
Valarie Zeithaml, A., Parasuraman, A., Berry, L.L.: Total, quality Management services. Diaz de Santos, Bogota (1993)
Sitto, K., Presser, M.: Field Guide to Hadoop, pp. 31–33. O’REILLY, Sebastopol (2015)
Sosinsky, B.: Cloud Computing Bible, p. 3. Wiley, Indianapolis (2011)
Stanford-Clark, A., Truong, H.: MQTT-SN Specification (2015). http://mqtt.org/new/wp-content/uploads/2009/06/MQTT-SN_spec_v1.2.pdf
Lezama, O.B.P., Izquierdo, N.V., Fernández, D.P., Dorta, R.L.G., Viloria, A., Marín, L.R.: Models of multivariate regression for labor accidents in different production sectors: comparative study. In: Tan, Y., Shi, Y., Tang, Q. (eds.) DMBD 2018. LNCS, vol. 10943. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93803-5_5
Izquierdo, N.V., Lezama, O.B.P., Dorta, R.G., Viloria, A., Deras, I., Hernández-Fernández, L.: Fuzzy logic applied to the performance evaluation. Honduran coffee sector case. In: Tan, Y., Shi, Y., Tang, Q. (eds.) ICSI 2018. LNCS, vol. 10942, pp. 164–173. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93818-9_16
Pineda Lezama, O., Gómez Dorta, R.: Techniques of multivariate statistical analysis: an application for the Honduran banking sector. Innovare J. Sci. Technol. 5(2), 61–75 (2017)
Viloria, A., Lis-Gutiérrez, J.P., Gaitán-Angulo, M., Godoy, A.R.M., Moreno, G.C., Kamatkar, S.J.: Methodology for the design of a student pattern recognition tool to facilitate the teaching - learning process through knowledge data discovery (Big data). In: Tan, Y., Shi, Y., Tang, Q. (eds.) DMBD 2018. LNCS, vol. 10943. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93803-5_63
Zhu, J., et al.: IBM cloud computing powering a smarter planet. In: Jaatun, M.G., Zhao, G., Rong, C. (eds.) CloudCom 2009. LNCS, vol. 5931, pp. 621–625. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-10665-1_62
Rodríguez, N., Chávez, S.B., Martin, A.E., Murazzo, M.A., Valenzuela, A.: Interoperabilidad en cloud computing. In: WICC 2011. Rosario, Argentina (2011)
Murazzo, M.A., Rodríguez, N.R., Villafañe, D.A., Gallardo, D.: Desarrollo de aplicaciones colaborativas para cloud computing. In: CACIC 2013. Mar del Plata, Argentina (2013)
Li, Q., Wang, Z.Y., Du, R.Y.: Applications integration in a hybrid cloud computing environment: modelling and platform. Enterp. Inf. Syst. 7(3), 237–271 (2013)
Toro, E.M., Mejia, D.A., Salazar, H.: Pronóstico de ventas usando redes neuronales. Scientia et technica 10(26), 25–30 (2004)
Villada, F., Muñoz, N., García, E.: Aplicación de las Redes Neuronales al Pronóstico de Precios en Mercado de Valores. Información tecnológica 23(4), 11–20 (2012)
Wen, Q., Mu, W., Sun, L., Hua, S., Zhou, Z.: Daily sales forecasting for grapes by support vector machine. In: Li, D., Chen, Y. (eds.) CCTA 2013. IAICT, vol. 420, pp. 351–360. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-642-54341-8_37
Wu, Q., Yan, H.S., Yang, H.B.: A forecasting model based support vector machine and particle swarm optimization. In: 2008 Workshop on Power Electronics and Intelligent Transportation System, pp. 218–222 (2008)
Ellingwood, J.: Apache vs Nginx: Practical Considerations (2015). https://www.digitalocean.com/community/tutorials/apache-vs-nginx-practical-considerations
Gilberth, S., Lynch, N.: Perspectives on the CAP theorem. Computer 45, 30–36 (2012)
Gouda, K., Patro, A., Dwivedi, D., Bhat, N.: Virtualization approaches in cloud computing. Int. J. Comput. Trends Technol. (IJCTT) 12, 161–166 (2014)
Hernández, D., Mazón, B., Campoverde, A.: Cloud Computing para el Internet de las Cosas. Caso de estudio orientado a la agricultura de precisión: I Congreso Internacional de Ciencia y tecnología UTMACH 2015. HiveMQ 2015. Paradigma de mensajería PUB/SUB. ISBN 978-9942-21-149-1 (2015). http://www.hivemq.com/mqtt-essentials-part2-publish-subscribe/
Karagiannis, V., Chatzimisios, P., Vazques, F., Zarate, J.: A survey on application layer protocols for the Internet of Things. Trans. IoT Cloud Comput. 3, 11–17 (2015)
Balachandran, B.M.: Development of a decision support system for hybrid and cloud computing. In: Intelligent Decision Technologies: Proceedings of the 5th KES International Conference on Intelligent Decision Technologies (KES-IDT 2013), vol. 255, p. 187. Courier Dover Publications, Junio (2013)
OpenStack. Introduction to OpenStack, Chapter 2. Brief Overview. http://docs.openstack.org/training-guides/content/module001-ch002-brief-overview.html
OpenStack. Introduction to OpenStack, Chapter 4. OpenStack Architecture. http://docs.openstack.org/training-guides/content/module001-ch004-openstack-architecture.html
Vazquez, C., Huedo, E., Montero, R., Llorente, I.: Elastic management of cluster-based services in the cloud. In: 1st workshop on Automated control for datacenters and clouds (ACDC 2009), pp. 19–24. ACM Digital Library, New York (2009)
Blanco, C.V., Huedo, E., Montero, R., Llorente, I.: Dynamic provision of computing resources from grid infrastructures and cloud providers. In: 2009 Workshops at the Grid and Pervasive Computing Conference, GPC 2009, pp. 113–120. IEEE Society Press, Geneva (2009)
Velte, T., Velte, A., Velte, T.J., Elsenpeter, R.: Cloud Computing: A Practical Approach. McGraw Hill Professional, New York (2009)
Reese, G.: Cloud Application Architectures, O’Relly (2009)
Chen, W., Lu, H., Shen, L., Wang, Z., Xiao, N., Chen, D.: A novel hardware assisted full virtualization technique. In: 9th International Conference for Young Computer Scientists, pp. 1292–1297 (2008)
Adams, K., Agesen, O.: A comparison of software and hardware techniques for x86 virtualization. In: Twelfth International Conference on Architectural Support for Programming Languages and Operating Systems (2006)
VMware: Understanding full virtualization, paravirtualization and hardware assist. Reporte Técnico (2007). http://www.vmware.com/resources/techresources/1008
Kernel Based Virtual Machine (KVM). http://www.linux-kvm.org/page/Main_Page
Nurmi, D., et al.: The eucalyptus open-source cloud-computing system. In: 9th IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID 2009), pp. 124–131. IEEE Computer Society, Washington (2009)
Red Hat: Red Hat Launches OpenShift Platform as a Service. http://www.eweek.com/c/a/Cloud-Computing/Red-Hat-Launches-OpenShift-Platform-as-a-Service-721913/)
Viloria, A., Gaitan-Angulo, M.: Statistical adjustment module advanced optimizer planner and SAP generated the case of a food production company. Indian J. Sci. Technol. 9(47) (2016). https://doi.org/10.17485/ijst/2016/v9i47/107371
Buyya, R., Beloglazov, A., Abawajy, J.: Energy-efficient management of data center resources for cloud computing: a vision, architectural elements, and open challenges. In: 2010 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 2010), Las Vegas (2010)
Berl, A., et al.: Energy-efficient cloud computing. Comput. J. 53(7), 1045–1051 (2010)
Zhang, F., Cao, J., Hwang, K., Wu, C.: Ordinal optimized scheduling of scientific workflows in elastic compute clouds. http://www.mit.edu/~caoj/pub/doc/jcao_j_ioo.pdf (2011)
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Viloria, A. et al. (2019). Hybrid Cloud Computing Architecture Based on Open Source Technology. In: Wang, G., Bhuiyan, M.Z.A., De Capitani di Vimercati, S., Ren, Y. (eds) Dependability in Sensor, Cloud, and Big Data Systems and Applications. DependSys 2019. Communications in Computer and Information Science, vol 1123. Springer, Singapore. https://doi.org/10.1007/978-981-15-1304-6_16
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