A Model-Driven Framework for Automated Generation and Verification of Cloud Solutions from Requirements View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-11-07

AUTHORS

Hamid R. Motahari Nezhad , Taiga Nakamura , Adi Sosnovich , Peifeng Yin , Karen Yorav

ABSTRACT

Cloud computing projects require the design of a so-called Cloud Solution, which is an architectural blueprint for a particular cloud environment. A cloud solution defines the hosting infrastructure (servers, VMs, etc.), software stack, and services such as network, backup, disaster recovery, management, etc. The design of a cloud solution needs to consider existing client environments and future environment’s requirements, and at the same time comply with the cloud provider’s portfolio and limitations. As such, the design of enterprise cloud solutions is a very complex and challenging problem. In this paper, we present a novel framework for provider-side cloud solution design based on model-driven and formal methods that facilitates the job of automated solution generation, starting from client requirements and resulting in a complete and correct cloud solution. We present a set of novel methods and a tool, called COOL, which implements the method and is used in production in a large Cloud service provider. More... »

PAGES

714-721

References to SciGraph publications

  • 2014. TOSCA: Portable Automated Deployment and Management of Cloud Applications in ADVANCED WEB SERVICES
  • 2017. Solving Constraint Satisfaction Problems Containing Vectors of Unknown Size in PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING
  • 2014-04. Strategies and Methods for Cloud Migration in INTERNATIONAL JOURNAL OF AUTOMATION AND COMPUTING
  • 2017. COOL: A Model-Driven and Automated System for Guided and Verifiable Cloud Solution Design in SERVICE-ORIENTED COMPUTING – ICSOC 2016 WORKSHOPS
  • Book

    TITLE

    Service-Oriented Computing

    ISBN

    978-3-030-03595-2
    978-3-030-03596-9

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-030-03596-9_51

    DOI

    http://dx.doi.org/10.1007/978-3-030-03596-9_51

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1108060027


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