3,583 research outputs found

    CYCLONE Unified Deployment and Management of Federated, Multi-Cloud Applications

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    Various Cloud layers have to work in concert in order to manage and deploy complex multi-cloud applications, executing sophisticated workflows for Cloud resource deployment, activation, adjustment, interaction, and monitoring. While there are ample solutions for managing individual Cloud aspects (e.g. network controllers, deployment tools, and application security software), there are no well-integrated suites for managing an entire multi cloud environment with multiple providers and deployment models. This paper presents the CYCLONE architecture that integrates a number of existing solutions to create an open, unified, holistic Cloud management platform for multi-cloud applications, tailored to the needs of research organizations and SMEs. It discusses major challenges in providing a network and security infrastructure for the Intercloud and concludes with the demonstration how the architecture is implemented in a real life bioinformatics use case

    SeaClouds: An Open Reference Architecture for Multi-Cloud Governance

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    A. Brogi, J. Carrasco, J. Cubo, F. D'Andria, E. Di Nitto, M. Guerriero, D. Pérez, E. Pimentel, J. Soldani. "SeaClouds: An Open Reference Architecture for Multi-Cloud Governance". In B. Tekinerdogan et al. (Eds.): ECSA 2016, LNCS 9839, pp. 334–338, 2016.We present the open reference architecture of the SeaClouds solution. It aims at enabling a seamless adaptive multi-cloud management of complex applications by supporting the distribution, monitoring and reconfiguration of app modules over heterogeneous cloud providers.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

    Proactive cloud management for highly heterogeneous multi-cloud infrastructures

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    Various literature studies demonstrated that the cloud computing paradigm can help to improve availability and performance of applications subject to the problem of software anomalies. Indeed, the cloud resource provisioning model enables users to rapidly access new processing resources, even distributed over different geographical regions, that can be promptly used in the case of, e.g., crashes or hangs of running machines, as well as to balance the load in the case of overloaded machines. Nevertheless, managing a complex geographically-distributed cloud deploy could be a complex and time-consuming task. Autonomic Cloud Manager (ACM) Framework is an autonomic framework for supporting proactive management of applications deployed over multiple cloud regions. It uses machine learning models to predict failures of virtual machines and to proactively redirect the load to healthy machines/cloud regions. In this paper, we study different policies to perform efficient proactive load balancing across cloud regions in order to mitigate the effect of software anomalies. These policies use predictions about the mean time to failure of virtual machines. We consider the case of heterogeneous cloud regions, i.e regions with different amount of resources, and we provide an experimental assessment of these policies in the context of ACM Framework

    A Multi-Cloud Warm-Absorber Model for NGC 4051

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    A multi-cloud model is presented which explains the soft X-ray excess in NGC 4051 and, consistently, the optical line spectrum and the SED of the continuum. The clouds are heated and ionized by the photoionizing flux from the active center and by shocks. Diffuse radiation, partly absorbed throughout the clouds, nicely fits the bump in the soft X-ray domain, while bremsstrahlung radiation from the gaseous clouds contribute to the fit of the continuum SED. Debris of high density fragmented clouds are necessary to explain the absorption oxygen throats observed at 0.87 keV and 0.74 keV. The debris are heated by shocks of about 200-300 km/s. Low velocity (100 km/s)-density (100 cm-3) clouds contribute to the line and continuum spectra, as well as high velocity (1000 km/s)-density (8000 cm-3) clouds which are revealed by the FWHM of the line profiles. The SED in the IR is explained by reradiation of dust, however, the dust-to-gas ratio is not particularly high. Radio emission is well fitted by synchrotron radiation created at the shock front by Fermi mechanism.Comment: 19 pages + 3 figures PostScrip

    PROACTIVE EXCHANGE OF DATA BETWEEN CLOUD PROVIDERS VIA CONTROLLER COORDINATION AND TRIGGER DYNAMIC WORKFLOWS

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    A multi-cloud Software Defined Network (SDN) controller proactively learns insights about subscribers, such as enterprise users, end users, and/or other cloud providers. Based on the learned insights, the multi-SDN controller applies dynamic policies on other cloud provides to which those subscribers are attached to. The multi-cloud SDN controller co-ordinates with various cloud providers, enterprise network controllers, and Internet Service Providers (ISPs) to proactively notify other cloud providers with information about affected users so that those providers can install additional resources at cloud edge/core on the fly. Additionally, the multi-cloud SDN controller facilitates a warm hand off from one cloud region to another cloud region. When the multi-cloud SDN controller learns about an enterprise outage, it proactively notifies other cloud providers of the outage event and the other cloud providers can use this for a warm hand off of session to the region(s) through which the users will be reconnected. The likely regions are derived based on telemetry obtained from multi-cloud SDN controller. The multi-cloud SDN controller also triggers a proactive cleanup of user context of the cloud provider side. The cloud provider cleans up after the connection reset event based on information from the multi-cloud SDN controller, rather than wait on a timeout of the connection

    Supporting Multi-Cloud in Serverless Computing

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    Serverless computing is a widely adopted cloud execution model composed of Function-as-a-Service (FaaS) and Backend-as-a-Service (BaaS) offerings. The increased level of abstraction makes vendor lock-in inherent to serverless computing, raising more concerns than previous cloud paradigms. Multi-cloud serverless is a promising emerging approach against vendor lock-in, yet multiple challenges must be overcome to tap its potential. First, we need to be aware of both the performance and cost of each FaaS provider. Second, a multi-cloud architecture must be proposed before deploying a multi-cloud workflow. Domain-specific serverless offerings must then be integrated into the multi-cloud architecture to improve performance or save costs. Moreover, dealing with serverless offerings from multiple providers is challenging. Finally, we require workload portability support for serverless multi-cloud. In this paper, we present a multi-cloud library for cross-serverless offerings. We develop the End Analysis System (EAS) to support comparison among public FaaS providers in terms of performance and cost. Moreover, we design proof-of-concept multi-cloud architectures with domain-specific serverless offerings to alleviate problems such as data gravity. Finally, we deploy workloads on these architectures to evaluate several public FaaS offerings.Comment: Accepted for the 15th IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC'22 Companion
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