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Dynamic Patterns for Cloud Application Life-Cycle Management

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Advances on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC 2019)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 96))

Abstract

Cloud applications are by nature dynamic and must react to variations in use, and evolve to adopt new Cloud services, and exploit new capabilities offered by Edge and Fog devices, or within data centers offering Graphics Processing Units (GPUs) or dedicated processors for Artificial Intelligence (AI). Our proposal is to alleviate this complexity by using patterns at all stages of the Cloud application life-cycle: deployment, automatic service discovery, monitoring, and adaptive application evolution. The main idea of this paper is that it is possible to reduce the complexity of composing, deploying, and evolving Cross-Cloud applications using dynamic patterns.

This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 731664 MELODIC: Multi-cloud execution-ware for large-scale optimised data-intensive computing; and grant agreement No. 731533 DECIDE: Multicloud applications towards the digital single market.

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Notes

  1. 1.

    https://www.iqvis.com/blog/cloud-computing-predictions-2020/.

  2. 2.

    https://melodic.cloud/.

  3. 3.

    https://www.decide-h2020.eu/.

  4. 4.

    https://www.w3.org/TR/owl2-overview/.

  5. 5.

    https://www.w3.org/.

  6. 6.

    https://www.w3.org/Submission/OWL-S/.

  7. 7.

    https://www.ieee.org/.

  8. 8.

    https://standards.ieee.org/project/2302.html.

  9. 9.

    https://octopus.com/.

  10. 10.

    https://www.ibm.com/support/knowledgecenter/en/linuxonibm/liaag/wecm/l0wecm00_was_deployment_manager.htm.

  11. 11.

    https://cloud.google.com/deployment-manager/.

  12. 12.

    https://kubernetes.io/.

  13. 13.

    https://web.cloudmore.com/.

  14. 14.

    https://www.computenext.com/platform/enterprise-cloud-brokerage.

  15. 15.

    http://www.nephostechnologies.com/technology/hybrid-cloud-management/.

  16. 16.

    https://www.intercloud.com/platform/overview.

  17. 17.

    https://www.ibm.com/us-en/marketplace/cloud-brokerage-solutions.

  18. 18.

    https://www.jamcracker.com/.

  19. 19.

    https://www.decide-h2020.eu.

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Author information

Authors and Affiliations

  1. University of Oslo, P.O. Box 1080 Blindern, 0316, Oslo, Norway

    Geir Horn

  2. Fundacion TECNALIA Research and Innovation, Derio, Spain

    Leire Orue-Echevarria Arrieta

  3. University of Campania “Luigi Vanvitelli”, Caserta, Italy

    Beniamino Di Martino

  4. 7Bulls.com, Al. Szucha 8, 00-582, Warsaw, Poland

    Paweł Skrzypek

  5. University of Piraeus, Piraeus, Greece

    Dimosthenis Kyriazis

Authors
  1. Geir Horn
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  2. Leire Orue-Echevarria Arrieta
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  3. Beniamino Di Martino
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  4. Paweł Skrzypek
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  5. Dimosthenis Kyriazis
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Correspondence to Geir Horn .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. University of Antwerp, Antwerpen, Belgium

    Peter Hellinckx

  3. Chiang Mai University, Chiang Mai, Thailand

    Juggapong Natwichai

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Horn, G., Arrieta, L.OE., Di Martino, B., Skrzypek, P., Kyriazis, D. (2020). Dynamic Patterns for Cloud Application Life-Cycle Management. In: Barolli, L., Hellinckx, P., Natwichai, J. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2019. Lecture Notes in Networks and Systems, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-030-33509-0_59

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  • DOI: https://doi.org/10.1007/978-3-030-33509-0_59

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