- -

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 completo del ítem

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

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/120659

Ficheros en el ítem

Metadatos del ítem

Título: Orchestrating Complex Application Architectures in Heterogeneous Clouds
Autor: Caballer Fernández, Miguel Zala, Sahdev López, Álvaro Moltó, Germán Orviz, Pablo Velten, Mathieu
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Universitat Politècnica de València. Instituto de Instrumentación para Imagen Molecular - Institut d'Instrumentació per a Imatge Molecular
Fecha difusión:
Resumen:
[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 ...[+]
Palabras clave: Cloud-computing , Heterogeneous-cloud , Multi-cloud , Open-source , TOSCA
Derechos de uso: Reserva de todos los derechos
Fuente:
Journal of Grid Computing. (issn: 1570-7873 )
DOI: 10.1007/s10723-017-9418-y
Editorial:
Springer-Verlag
Versión del editor: http://doi.org/10.1007/s10723-017-9418-y
Código del Proyecto:
info:eu-repo/grantAgreement/EC/H2020/653549/EU/INtegrating Distributed data Infrastructures for Global ExplOitation/
Agradecimientos:
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.
Tipo: Artículo

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)

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

Amazon Web Services (AWS): Amazon Web Services (AWS). https://aws.amazon.com/ (2017) [+]
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)

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

Amazon Web Services (AWS): Amazon Web Services (AWS). https://aws.amazon.com/ (2017)

Amazon Web Services (AWS): CloudFormation. https://aws.amazon.com/cloudformation/ (2017)

Apache Software Foundation: Apache Mesos. http://mesos.apache.org/ (2017)

ARIA, ARIA. http://ariatosca.incubator.apache.org/ (2017)

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)

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

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

Celar: Celar. http://www.cloudwatchhub.eu/celar (2017)

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)

Chronos: Chronos. https://mesos.github.io/chronos/ (2017)

Cloudify: Cloudify. http://getcloudify.org (2017)

Davidović, D., Cetinić, E., Skala, K.: European research area and digital humanities

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

EGI FedCloud: EGI FedCloud. https://www.egi.eu/federation/egi-federated-cloud/ (2017)

Eucalyptus: Eucalyptus. https://www.eucalyptus.com/ (2017)

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

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)

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)

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)

Google Cloud Platform (GCP): Google Cloud Platform (GCP). https://cloud.google.com/ (2017)

Hochstein, L. (ed.): Ansible: Up and Running, Automating Configuration Management and Deployment the Easy Way. O’Reilly Media (2014)

Idabc: European Interoperability Framework for pan-European eGovernment Services. European Commission version 1, 1–25. https://doi.org/10.1109/HICSS.2007.68 (2004)

IM: IM. http://www.grycap.upv.es/im (2017)

INDIGO-DataCloud: D1.8 - General Architecture. Tech. rep., INDIGO-DataCloud Consortium (2015)

INDIGO-DataCloud: Ansible Galaxy repository for INDIGO-DataCloud. https://galaxy.ansible.com/indigo-dc/ (2017)

INDIGO-DataCloud: Disvis/Powerfit Ansible Role in Ansible Galaxy. https://galaxy.ansible.com/indigo-dc/disvis-powerfit/ (2017)

INDIGO-DataCloud: INDIGO-DataCloud. https://www.indigo-datacloud.eu/ (2017)

INDIGO-DataCloud: INDIGO-DataCloud DockerHub application repository. https://hub.docker.com/u/indigodatacloudapps/ (2017)

INDIGO-DataCloud: INDIGO-DataCloud PaaS Orchestrator. https://github.com/indigo-dc/orchestrator (2017)

INDIGO-DataCloud: INDIGO-DataCloud RepoSync. https://github.com/indigo-dc/java-reposync (2017)

INDIGO-DataCloud: INDIGO-DataCloud TOSCA templates. https://github.com/indigo-dc/tosca-templates (2017)

INDIGO-DataCloud: TOSCA Across Clouds. https://github.com/indigo-dc/tosca-types/blob/master/examples/web_mysql_tosca_across_clouds.yaml (2017)

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)

INDIGO-DataCloud: TOSCA template for Powerfit application. https://github.com/indigo-dc/tosca-types/blob/master/examples/powerfit.yaml (2017)

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)

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)

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)

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

Kurkcuoglu Soner, Z., Bonvin, A.: Science in the clouds: virtualizing haddock powerfit and disvis using indigo-datacloud solutions (2016)

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)

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)

López García, Á., Fernández-del Castillo, E.: Analysis of scientific cloud computing requirements. In: Proceedings of the IBERGRID 2013 Conference, p 147 158 (2013)

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

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)

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

Marathon: Marathon. https://mesosphere.github.io/marathon/ (2017)

Metsch, T., Edmonds, A.: Open Cloud Computing Interface-Infrastructure. Tech. rep., Open Grid Forum (2010)

Metsch, T., Edmonds, A.: Open Cloud Computing Interface-RESTful HTTP Rendering. Tech. rep., Open Grid Forum (2011)

Microsoft Azure: Microsoft Azure. https://azure.microsoft.com/ (2017)

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)

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)

Nyrén, R., Metsch, T., Edmonds, A., Papaspyrou, A.: Open Cloud Computing Interface–Core. Tech. rep., Open Grid Forum (2010)

OASIS: Organization for the Advancement of Structured Information Standards (OASIS). https://www.oasis-open.org (2015)

Open Telekom Cloud (OTC): Open Telekom Cloud (OTC). https://cloud.telekom.de/en/ (2017)

OpenNebula: OneFlow. http://docs.opennebula.org/5.2/advanced_components/application_flow_and_auto-scaling/index.html (2017)

OpenNebula Project: OpenNebula. https://www.opennebula.org (2017)

OpenStack Foundation: Heat Orchestration Template (HOT) Guide. https://docs.openstack.org/heat/latest/template_guide/hot_guide.html (2017)

OpenStack Foundation: OpenStack. https://www.openstack.org (2017)

OpenStack Foundation: Openstack Heat. http://wiki.openstack.org/wiki/Heat (2017)

OpenStack Foundation: OpenStack Heat Translator. https://github.com/openstack/heat-translator (2017)

OpenStack Foundation: OpenStack heat-translator project contribution statistics. http://stackalytics.com/?release=all&metric=commits&module=heat-translator (2017)

OpenStack Foundation: OpenStack Tacker. https://wiki.openstack.org/wiki/Tacker (2017)

OpenStack Foundation: OpenStack tosca-parser project contribution statistics. http://stackalytics.com/?release=all&metric=commits&module=tosca-parser (2017)

OpenStack Foundation: TOSCA Parser. https://github.com/openstack/tosca-parser (2017)

OpenTOSCA: OpenTOSCA. http://www.opentosca.org/ (2017)

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)

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)

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

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

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)

Python: Python Package Index (PyPI). https://pypi.python.org/pypi (2017)

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)

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)

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)

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

SlipStream: SlipStream. http://sixsq.com/products/slipstream/ (2017)

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

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)

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

UK Government Cabinet Office: Open Standards Principles. https://www.gov.uk/government/publications/open-standards-principles/open-standards-principles (2015)

Yangui, S., Marshall, I.J., Laisne, J.P., Tata, S.: Compatibleone: the open source cloud broker. J Grid Comput. 12(1), 93–109 (2014)

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

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

[-]

recommendations

 

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

Mostrar el registro completo del ítem