- -

Orchestrating Complex Application Architectures in Heterogeneous Clouds

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Orchestrating Complex Application Architectures in Heterogeneous Clouds

Mostrar el registro sencillo del ítem

Ficheros en el ítem

Thumbnail
Nombre: SVJour3__Springer ...
Tamaño: 1.540Mb
Formato: PDF
Descripción: Versión del Autor.
Abrir
[Cerrado]
Nombre: Caballer2018_Arti ...
Tamaño: 2.144Mb
Formato: PDF
Descripción: Versión editorial
Solicitar una copia al autor
dc.contributor.author Caballer Fernández, Miguel es_ES
dc.contributor.author Zala, Sahdev es_ES
dc.contributor.author López, Álvaro es_ES
dc.contributor.author Moltó, Germán es_ES
dc.contributor.author Orviz, Pablo es_ES
dc.contributor.author Velten, Mathieu es_ES
dc.date.accessioned 2019-05-18T20:38:22Z
dc.date.available 2019-05-18T20:38:22Z
dc.date.issued 2018 es_ES
dc.identifier.issn 1570-7873 es_ES
dc.identifier.uri http://hdl.handle.net/10251/120659
dc.description.abstract [EN] Private cloud infrastructures are now widely deployed and adopted across technology industries and research institutions. Although cloud computing has emerged as a reality, it is now known that a single cloud provider cannot fully satisfy complex user requirements. This has resulted in a growing interest in developing hybrid cloud solutions that bind together distinct and heterogeneous cloud infrastructures. In this paper we describe the orchestration approach for heterogeneous clouds that has been implemented and used within the INDIGO-DataCloud project. This orchestration model uses existing open-source software like OpenStack and leverages the OASIS Topology and Specification for Cloud Applications (TOSCA) open standard as the modeling language. Our approach uses virtual machines and Docker containers in an homogeneous and transparent way providing consistent application deployment for the users. This approach is illustrated by means of two different use cases in different scientific communities, implemented using the INDIGO-DataCloud solutions. es_ES
dc.description.sponsorship The authors want to acknowledge the support of the INDIGO-Datacloud (grant number 653549) project, funded by the European Commission's Horizon 2020 Framework Program. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Journal of Grid Computing es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Cloud-computing es_ES
dc.subject Heterogeneous-cloud es_ES
dc.subject Multi-cloud es_ES
dc.subject Open-source es_ES
dc.subject TOSCA es_ES
dc.subject.classification CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL es_ES
dc.title Orchestrating Complex Application Architectures in Heterogeneous Clouds es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10723-017-9418-y es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/653549/EU/INtegrating Distributed data Infrastructures for Global ExplOitation/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Instrumentación para Imagen Molecular - Institut d'Instrumentació per a Imatge Molecular es_ES
dc.description.bibliographicCitation Caballer Fernández, M.; Zala, S.; López, Á.; Moltó, G.; Orviz, P.; Velten, M. (2018). Orchestrating Complex Application Architectures in Heterogeneous Clouds. Journal of Grid Computing. 16(1):3-18. https://doi.org/10.1007/s10723-017-9418-y es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1007/s10723-017-9418-y es_ES
dc.description.upvformatpinicio 3 es_ES
dc.description.upvformatpfin 18 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 16 es_ES
dc.description.issue 1 es_ES
dc.relation.pasarela S\345945 es_ES
dc.contributor.funder European Commission es_ES
dc.description.references Aguilar Gómez, F., de Lucas, J.M., García, D., Monteoliva, A.: Hydrodynamics and water quality forecasting over a cloud computing environment: indigo-datacloud. In: EGU General Assembly Conference Abstracts, vol. 19, p 9684 (2017) es_ES
dc.description.references de Alfonso, C., Caballer, M., Alvarruiz, F., Hernández, V.: An energy management system for cluster infrastructures. Comput. Electr. Eng. 39(8), 2579–2590 (2013). http://www.sciencedirect.com/science/article/pii/S0045790613001365 es_ES
dc.description.references Amazon Web Services (AWS): Amazon Web Services (AWS). https://aws.amazon.com/ (2017) es_ES
dc.description.references Amazon Web Services (AWS): CloudFormation. https://aws.amazon.com/cloudformation/ (2017) es_ES
dc.description.references Apache Software Foundation: Apache Mesos. http://mesos.apache.org/ (2017) es_ES
dc.description.references ARIA, ARIA. http://ariatosca.incubator.apache.org/ (2017) es_ES
dc.description.references Bumpus, W.: NIST Cloud Computing Standards Roadmap. Tech. rep., National Institute of Standards and Technology (NIST). https://doi.org/10.6028/NIST.SP.500-291r2 (2013) es_ES
dc.description.references Caballer, M., Blanquer, I., Moltó, G., de Alfonso, C.: Dynamic management of virtual infrastructures. J Grid Comput. 13(1), 53–70 (2015). https://doi.org/10.1007/s10723-014-9296-5 es_ES
dc.description.references Campos Plasencia, I., Fernández-del Castillo, E., Heinemeyer, S., López García, Á., Pahlen, F., Borges, G.: Phenomenology tools on cloud infrastructures using OpenStack. Eur. Phys. J. C 73(4), 2375 (2013). https://doi.org/10.1140/epjc/s10052-013-2375-0 es_ES
dc.description.references Celar: Celar. http://www.cloudwatchhub.eu/celar (2017) es_ES
dc.description.references Chen, Y., de Lucas, J.M., Aguilar, F., Fiore, S., Rossi, M., Ferrari, T.: Indigo: building a datacloud framework to support open science. In: EGU General Assembly Conference Abstracts, vol. 18, p 16610 (2016) es_ES
dc.description.references Chronos: Chronos. https://mesos.github.io/chronos/ (2017) es_ES
dc.description.references Cloudify: Cloudify. http://getcloudify.org (2017) es_ES
dc.description.references Davidović, D., Cetinić, E., Skala, K.: European research area and digital humanities es_ES
dc.description.references Distefano, S., Serazzi, G.: Performance driven WS orchestration and deployment in service oriented infrastructure. J Grid Comput. 12(2), 347–369 (2014). https://doi.org/10.1007/s10723-014-9293-8 es_ES
dc.description.references EGI FedCloud: EGI FedCloud. https://www.egi.eu/federation/egi-federated-cloud/ (2017) es_ES
dc.description.references Eucalyptus: Eucalyptus. https://www.eucalyptus.com/ (2017) es_ES
dc.description.references Fiore, S., D’Anca, A., Palazzo, C., Foster, I., Williams, D.N., Aloisio, G.: Ophidia: toward big data analytics for eScience. Procedia Comput. Sci. 18, 2376–2385 (2013). https://doi.org/10.1016/j.procs.2013.05.409 es_ES
dc.description.references Fiore, S., Palazzo, C., D’Anca, A., Elia, D., Londero, E., Knapic, C., Monna, S., Marcucci, N.M., Aguilar, F., Płóciennik, M., et al.: Big data analytics on large-scale scientific datasets in the indigo-datacloud project. In: Proceedings of the Computing Frontiers Conference, pp 343–348. ACM (2017) es_ES
dc.description.references Fiore, S., Płóciennik, M., Doutriaux, C., Palazzo, C., Boutte, J., żok, T., Elia, D., Owsiak, M., D’Anca, A., Shaheen, Z., et al.: Distributed and cloud-based multi-model analytics experiments on large volumes of climate change data in the earth system grid federation eco-system. In: 2016 IEEE International Conference on Big Data (Big Data), pp 2911–2918. IEEE (2016) es_ES
dc.description.references Galante, G., Erpen de Bona, L.C., Mury, A.R., Schulze, B., da Rosa Righi, R.: An analysis of public clouds elasticity in the execution of scientific applications: a survey. J Grid Comput.,1–24. https://doi.org/10.1007/s10723-016-9361-3 (2016) es_ES
dc.description.references Google Cloud Platform (GCP): Google Cloud Platform (GCP). https://cloud.google.com/ (2017) es_ES
dc.description.references Hochstein, L. (ed.): Ansible: Up and Running, Automating Configuration Management and Deployment the Easy Way. O’Reilly Media (2014) es_ES
dc.description.references Idabc: European Interoperability Framework for pan-European eGovernment Services. European Commission version 1, 1–25. https://doi.org/10.1109/HICSS.2007.68 (2004) es_ES
dc.description.references IM: IM. http://www.grycap.upv.es/im (2017) es_ES
dc.description.references INDIGO-DataCloud: D1.8 - General Architecture. Tech. rep., INDIGO-DataCloud Consortium (2015) es_ES
dc.description.references INDIGO-DataCloud: Ansible Galaxy repository for INDIGO-DataCloud. https://galaxy.ansible.com/indigo-dc/ (2017) es_ES
dc.description.references INDIGO-DataCloud: Disvis/Powerfit Ansible Role in Ansible Galaxy. https://galaxy.ansible.com/indigo-dc/disvis-powerfit/ (2017) es_ES
dc.description.references INDIGO-DataCloud: INDIGO-DataCloud. https://www.indigo-datacloud.eu/ (2017) es_ES
dc.description.references INDIGO-DataCloud: INDIGO-DataCloud DockerHub application repository. https://hub.docker.com/u/indigodatacloudapps/ (2017) es_ES
dc.description.references INDIGO-DataCloud: INDIGO-DataCloud PaaS Orchestrator. https://github.com/indigo-dc/orchestrator (2017) es_ES
dc.description.references INDIGO-DataCloud: INDIGO-DataCloud RepoSync. https://github.com/indigo-dc/java-reposync (2017) es_ES
dc.description.references INDIGO-DataCloud: INDIGO-DataCloud TOSCA templates. https://github.com/indigo-dc/tosca-templates (2017) es_ES
dc.description.references INDIGO-DataCloud: TOSCA Across Clouds. https://github.com/indigo-dc/tosca-types/blob/master/examples/web_mysql_tosca_across_clouds.yaml (2017) es_ES
dc.description.references INDIGO-DataCloud: TOSCA template for deploying an Elastic Mesos Cluster. http://github.com/indigo-dc/tosca-types/blob/master/examples/mesos_elastic_cluster.yaml (2017) es_ES
dc.description.references INDIGO-DataCloud: TOSCA template for Powerfit application. https://github.com/indigo-dc/tosca-types/blob/master/examples/powerfit.yaml (2017) es_ES
dc.description.references Kacsuk, P., Kecskemeti, G., Kertesz, A., Nemeth, Z., Kovȧcs, J., Farkas, Z.: Infrastructure aware scientific workflows and infrastructure aware workflow managers in science gateways. J Grid Comput., 641–654. https://doi.org/10.1007/s10723-016-9380-0 (2016) es_ES
dc.description.references Korambath, P., Wang, J., Kumar, A., Hochstein, L., Schott, B., Graybill, R., Baldea, M., Davis, J.: Deploying kepler workflows as services on a cloud infrastructure for smart manufacturing. Procedia Comput. Sci. 29, 2254–2259 (2014) es_ES
dc.description.references Koski, K., Hormia-Poutanen, K., Chatzopoulos, M., Legrė, Y., Day, B.: Position Paper: European Open Science Cloud for Research. Tech. Rep. october, EUDAT, LIBER, OpenAIRE, EGI, GĖANT Bari (2015) es_ES
dc.description.references Krieger, M.T., Torreno, O., Trelles, O., Kranzlmüller, D.: Building an open source cloud environment with auto-scaling resources for executing bioinformatics and biomedical workflows. Futur. Gener. Comput. Syst. 67, 329–340 (2017). https://doi.org/10.1016/j.future.2016.02.008 es_ES
dc.description.references Kurkcuoglu Soner, Z., Bonvin, A.: Science in the clouds: virtualizing haddock powerfit and disvis using indigo-datacloud solutions (2016) es_ES
dc.description.references Lipton, P.C.T., Moser, S.I., Palma, D.V., Spatzier, T.I.: Topology and Orchestration Specification for Cloud Applications. Tech. rep., OASIS Standard (2013) es_ES
dc.description.references Liu, C., Mao, Y., Van der Merwe, J., Fernandez, M.: Cloud Resource Orchestration: a Data-Centric Approach. In: Proceedings of the Biennial Conference on Innovative Data Systems Research (CIDR), pp 1–8. Citeseer (2011) es_ES
dc.description.references López García, Á., Fernández-del Castillo, E.: Analysis of scientific cloud computing requirements. In: Proceedings of the IBERGRID 2013 Conference, p 147 158 (2013) es_ES
dc.description.references López García, Á., Fernández-del Castillo, E., Orviz Fernández, P.: Standards for enabling heterogeneous IaaS cloud federations. Comput. Standard Inter. 47, 19–23 (2016). https://doi.org/10.1016/j.csi.2016.02.002 es_ES
dc.description.references López García, Á., Zangrando, L., Sgaravatto, M., Llorens, V., Vallero, S., Zaccolo, V., Bagnasco, S., Taneja, S., Pra, S.D., Salomoni, D., Donvito G.: Improved cloud resource allocation: how INDIGO-datacloud is overcoming the current limitations in cloud schedulers. arXiv: 1707.06403 (2017) es_ES
dc.description.references Lorido-Botran, T., Miguel-Alonso, J., Lozano, J.A.: A review of auto-scaling techniques for elastic applications in cloud environments. J Grid Comput. 12(4), 559–592 (2014). https://doi.org/10.1007/s10723-014-9314-7 es_ES
dc.description.references Marathon: Marathon. https://mesosphere.github.io/marathon/ (2017) es_ES
dc.description.references Metsch, T., Edmonds, A.: Open Cloud Computing Interface-Infrastructure. Tech. rep., Open Grid Forum (2010) es_ES
dc.description.references Metsch, T., Edmonds, A.: Open Cloud Computing Interface-RESTful HTTP Rendering. Tech. rep., Open Grid Forum (2011) es_ES
dc.description.references Microsoft Azure: Microsoft Azure. https://azure.microsoft.com/ (2017) es_ES
dc.description.references Moltó, G., Caballer, M., Pérez, A., Alfonso, D.C., Blanquer, I.: Coherent application delivery on hybrid distributed computing infrastructures of virtual machines and docker containers. In: 2017 25Th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). https://doi.org/10.1109/PDP.2017.29 , pp 486–490 (2017) es_ES
dc.description.references Monna, S., Marcucci, N.M., Marinaro, G., Fiore, S., D’Anca, A., Antonacci, M., Beranzoli, L., Favali, P.: An Emso data case study within the indigo-Dc project. In: EGU General Assembly Conference Abstracts, vol. 19, p 12493 (2017) es_ES
dc.description.references Nyrén, R., Metsch, T., Edmonds, A., Papaspyrou, A.: Open Cloud Computing Interface–Core. Tech. rep., Open Grid Forum (2010) es_ES
dc.description.references OASIS: Organization for the Advancement of Structured Information Standards (OASIS). https://www.oasis-open.org (2015) es_ES
dc.description.references Open Telekom Cloud (OTC): Open Telekom Cloud (OTC). https://cloud.telekom.de/en/ (2017) es_ES
dc.description.references OpenNebula: OneFlow. http://docs.opennebula.org/5.2/advanced_components/application_flow_and_auto-scaling/index.html (2017) es_ES
dc.description.references OpenNebula Project: OpenNebula. https://www.opennebula.org (2017) es_ES
dc.description.references OpenStack Foundation: Heat Orchestration Template (HOT) Guide. https://docs.openstack.org/heat/latest/template_guide/hot_guide.html (2017) es_ES
dc.description.references OpenStack Foundation: OpenStack. https://www.openstack.org (2017) es_ES
dc.description.references OpenStack Foundation: Openstack Heat. http://wiki.openstack.org/wiki/Heat (2017) es_ES
dc.description.references OpenStack Foundation: OpenStack Heat Translator. https://github.com/openstack/heat-translator (2017) es_ES
dc.description.references OpenStack Foundation: OpenStack heat-translator project contribution statistics. http://stackalytics.com/?release=all&metric=commits&module=heat-translator (2017) es_ES
dc.description.references OpenStack Foundation: OpenStack Tacker. https://wiki.openstack.org/wiki/Tacker (2017) es_ES
dc.description.references OpenStack Foundation: OpenStack tosca-parser project contribution statistics. http://stackalytics.com/?release=all&metric=commits&module=tosca-parser (2017) es_ES
dc.description.references OpenStack Foundation: TOSCA Parser. https://github.com/openstack/tosca-parser (2017) es_ES
dc.description.references OpenTOSCA: OpenTOSCA. http://www.opentosca.org/ (2017) es_ES
dc.description.references Owsiak, M., Plociennik, M., Palak, B., Zok, T., Reux, C., Di Gallo, L., Kalupin, D., Johnson, T., Schneider, M.: Running simultaneous kepler sessions for the parallelization of parametric scans and optimization studies applied to complex workflows. J Comput. Sci. 20, 103–111 (2017) es_ES
dc.description.references Palma, D., Rutkowski, M., Spatzier T.: TOSCA Simple Profile in YAML Version 1.1. Tech. rep., OASIS Standard. http://docs.oasis-open.org/tosca/TOSCA-Simple-Profile-YAML/v1.1/TOSCA-Simple-Profile-YAML-v1.1.html (2016) es_ES
dc.description.references Petcu, D.: Consuming resources and services from multiple clouds: from terminology to cloudware support. J Grid Comput. 12(2), 321–345 (2014). https://doi.org/10.1007/s10723-013-9290-3 es_ES
dc.description.references Plóciennik, M., Fiore, S., Donvito, G., Owsiak, M., Fargetta, M., Barbera, R., Bruno, R., Giorgio, E., Williams, D.N., Aloisio, G.: Two-level dynamic workflow orchestration in the INDIGO DataCloud for large-scale, climate change data analytics experiments. Procedia Comput. Sci. 80, 722–733 (2016). https://doi.org/10.1016/j.procs.2016.05.359 es_ES
dc.description.references Płóciennik, M., Fiore, S., Donvito, G., Owsiak, M., Fargetta, M., Barbera, R., Bruno, R., Giorgio, E., Williams, D.N., Aloisio, G.: Two-level dynamic workflow orchestration in the indigo datacloud for large-scale, climate change data analytics experiments. Procedia Comput. Sci. 80, 722–733 (2016) es_ES
dc.description.references Python: Python Package Index (PyPI). https://pypi.python.org/pypi (2017) es_ES
dc.description.references Ramakrishnan, L., Jackson, K.R., Canon, S., Cholia, S., Shalf, J.: Defining future platform requirements for e-Science clouds. In: Proceedings of the 1st ACM Symposium on Cloud Computing - SoCC ’10. https://doi.org/10.1145/1807128.1807145 , p 101 (2010) es_ES
dc.description.references Ramakrishnan, L., Zbiegel, P.T.T.T.: Magellan: experiences from a science cloud. In: Proceedings of the 2Nd International Workshop on Scientific Cloud Computing. http://dl.acm.org/citation.cfm?id=1996119 , pp 49–58 (2011) es_ES
dc.description.references Salomoni, D., Campos, I., Gaido, L., Donvito, G., Antonacci, M., Fuhrman, P., Marco, J., Lopez-Garcia, A., Orviz, P., Blanquer, I., et al.: Indigo-datacloud: foundations and architectural description of a platform as a service oriented to scientific computing. arXiv: http://arXiv.org/abs/1603.09536 (2016) es_ES
dc.description.references Sánchez-Expósito, S., Martín, P., Ruiz, J.E., Verdes-Montenegro, L., Garrido, J., Sirvent, R., Falcó, A.R., Badia, R.M., Lezzi, D.: Web services as building blocks for science gateways in astrophysics. J Grid Comput. 14(4), 673–685 (2016). https://doi.org/10.1007/s10723-016-9382-y es_ES
dc.description.references SlipStream: SlipStream. http://sixsq.com/products/slipstream/ (2017) es_ES
dc.description.references Stockton, D.B., Santamaria, F.: Automating NEURON simulation deployment in cloud resources. Neuroinformatics 15(1), 51–70 (2017). https://doi.org/10.1007/s12021-016-9315-8 es_ES
dc.description.references Teckelmann, R., Reich, C., Sulistio, A.: Mapping of Cloud Standards to the Taxonomy of Interoperability in Iaas. In: 2011 IEEE Third International Conference on Cloud Computing Technology and Science (Cloudcom), pp 522–526. IEEE (2011) es_ES
dc.description.references Toor, S., Osmani, L., Eerola, P., Kraemer, O., Lindén, T., Tarkoma, S., White, J.: A scalable infrastructure for CMS data analysis based on OpenStack Cloud and Gluster file system. J Phys.: Conf. Ser. 513(6), 062,047 (2014). https://doi.org/10.1088/1742-6596/513/6/062047 . http://stacks.iop.org/1742-6596/513/i=6/a=062047?key=crossref.84033a04265ce343371c7f38064e7143 es_ES
dc.description.references UK Government Cabinet Office: Open Standards Principles. https://www.gov.uk/government/publications/open-standards-principles/open-standards-principles (2015) es_ES
dc.description.references Yangui, S., Marshall, I.J., Laisne, J.P., Tata, S.: Compatibleone: the open source cloud broker. J Grid Comput. 12(1), 93–109 (2014) es_ES
dc.description.references Zhao, Y., Li, Y., Raicu, I., Lu, S., Tian, W., Liu, H.: Enabling scalable scientific workflow management in the cloud. Futur. Gener. Comput. Syst. 46, 3–16 (2015). https://doi.org/10.1016/j.future.2014.10.023 es_ES
dc.description.references van Zundert, G., Trellet, M., Schaarschmidt, J., Kurkcuoglu, Z., David, M., Verlato, M., Rosato, A., Bonvin, A.: The DisVis and PowerFit web servers: explorative and integrative modeling of biomolecular complexes. J. Mol. Biol. 429(3), 399–407 (2013). http://www.sciencedirect.com/science/article/pii/S0022283616305277 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem