Feature-Based Configuration of Vendor-Independent Deployments on IaaS

Wittern, Erik; Lenk, Alexander; Bartenbach, Sebastian; Braeuer, Tobias

doi:10.1109/edoc.2014.26

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…Most orchestration techniques only support describing resources of a specific provider [Konstantinou and et al 2009;Wittern et al 2014;AWS 2013b]. On the other hand, others such as TOSCA, ModaClouds and CloudBase provide cross-provider cater for Resource Entities that are portable across different providers Ardagna and et al 2012;].…”

Section: Resource Entitymentioning

confidence: 99%

A Taxonomy and Survey of Cloud Resource Orchestration Techniques

et al. 2017

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Cloud services and applications prove indispensable amid today’s modern utility-based computing. The cloud has displayed a disruptive and growing impact on everyday computing tasks. However, facilitating the orchestration of cloud resources to build such cloud services and applications is yet to unleash its entire magnitude of power. Accordingly, it is paramount to devise a unified and comprehensive analysis framework to accelerate fundamental understanding of cloud resource orchestration in terms of concepts, paradigms, languages, models, and tools. This framework is essential to empower effective research, comprehension, comparison, and selection of cloud resource orchestration models, languages, platforms, and tools. This article provides such a comprehensive framework while analyzing the relevant state of the art in cloud resource orchestration from a novel and holistic viewpoint.

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Section: Resource Entitymentioning

confidence: 99%

A Taxonomy and Survey of Cloud Resource Orchestration Techniques

et al. 2017

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“…This section presents some efforts in the area of virtual disk image provisioning in context of SPL [7,11,12,13]. Among these researches, Wittern, Erik, et al [11] present an Infrastructure-as-a-Service (IaaS) deploy model to describe IaaS consumer requirements, including VMs, virtual disk images, and software installed on the images using feature model. Once IaaS consumer selects the cloud provider, VM type, and virtual disk image for the VM, deployment engine invokes a web service call to instantiate VM described in the selected IaaS deploy model.…”

Section: Related Workmentioning

confidence: 99%

Feature-Model-Based Commonality and Variability Analysis for Virtual Cluster Disk Provisioning

Cho¹,

Ku²,

Rui³

et al. 2016

Computer Science &Amp; Information Technology ( CS &Amp; IT )

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The rapid growth of networking and storage capacity allows collecting and analyzing massive amount of data by relying increasingly on scalable, flexible, and on-demand provisioned largescale computing resources. Virtualization is one of the feasible solution to provide large amounts of computational power with dynamic provisioning of underlying computing resources. Typically, distributed scientific applications for analyzing data run on cluster nodes to perform the same task in parallel. However, on-demand virtual disk provisioning for a set of virtual machines, called virtual cluster, is not a trivial task. This paper presents a feature model-based commonality and variability analysis system for virtual cluster disk provisioning to categorize types of virtual disks that should be provisioned. Also, we present an applicable case study to analyze common and variant software features between two different subgroups of the big data processing virtual cluster. Consequently, by using the analysis system, it is possible to provide an ability to accelerate the virtual disk creation process by reducing duplicate software installation activities on a set of virtual disks that need to be provisioned in the same virtual cluster.

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Cloud Standby: Disaster Recovery of Distributed Systems in the Cloud

Lenk

Tai

2014

Advanced Information Systems Engineering

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Disaster recovery planning and securing business processes against outtakes have been essential parts of running a company for decades. As IT systems became more important, and especially since more and more revenue is generated over the Internet, securing the IT systems that support the business processes against outages is essential. Using fully operational standby sites with periodically updated standby systems is a well-known approach to prepare against disasters. Setting up and maintaining a second datacenter is, however, expensive. In this work, we present Cloud Standby, a warm standby approach for setting up and updating a standby system in the Cloud. We describe the architecture of Cloud Standby and its methods for deploying and updating the standby system. We show that by using Cloud Standby the recovery time and long-term costs of disaster recovery can significantly be reduced.

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Feature-Based Configuration of Vendor-Independent Deployments on IaaS

Cited by 4 publications

References 19 publications

A Taxonomy and Survey of Cloud Resource Orchestration Techniques

A Taxonomy and Survey of Cloud Resource Orchestration Techniques

Feature-Model-Based Commonality and Variability Analysis for Virtual Cluster Disk Provisioning

Cloud Standby: Disaster Recovery of Distributed Systems in the Cloud

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