Virtualised e-Learning with real-time guarantees on the IRMOS platform

Cucinotta, Tommaso; Checconi, Fabio; Zlatev, Zlatko; Papay, Juri; Boniface, Michael; Kousiouris, George; Kyriazis, Dimosthenis; Varvarigou, Theodora; Berger, Sören; Lamp, Dominik; Mazzetti, A.; Voith, Thomas; Stein, Manuel

doi:10.1109/soca.2010.5707166

Cited by 24 publications

(24 citation statements)

References 20 publications

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“…Similarly, on the side of computing technologies, platforms for real-time and predictable computing are becoming increasingly accessible, not restricting to the traditional area of real-time and embedded systems, but recently spreading also over the area of predictable cloud computing [15] [29].…”

Section: Propositionmentioning

confidence: 99%

“…Other interesting results from the research carried out in IRMOS include: algorithms for the optimum placement of distributed virtualized applications with probabilistic end-to-end latency requirements [16]; the use of neural networks for estimating the performance of Virtual Machines execution under different scheduling configurations [18]; techniques for reduced down-time in live-migration of VMs with time-sensitive workloads [37]; and others. The effectiveness of IRMOS/ISONI has been demonstrated for example through an e-Learning demonstrator [15].…”

Section: Isolation Of Networkingmentioning

confidence: 99%

See 1 more Smart Citation

End-to-End Service Quality for Cloud Applications

Oberle

Cherubini

Cucinotta

2013

Economics of Grids, Clouds, Systems, and Services

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This paper aims to highlight the importance of end-to-end service quality for cloud services, with a focus on telecom carrier-grade services. In multi-tenant distributed and virtualized cloud infrastructures, the enhanced level of resource sharing raises issues in terms of performance stability and reliability of cloud services, threatening the possibility to offer precise service levels in end-to-end scenarios.

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Section: Propositionmentioning

confidence: 99%

Section: Isolation Of Networkingmentioning

confidence: 99%

End-to-End Service Quality for Cloud Applications

Oberle

Cherubini

Cucinotta

2013

Economics of Grids, Clouds, Systems, and Services

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“…However, the complexity of determining Quality of Service (QoS) requirements for applications in such environments introduces signi cant market ine ciencies and has driven the emergence of service engineering tools for modelling, analysing and planning the QoS of service based applications deployed within the Cloud [1,2].…”

Section: Introductionmentioning

confidence: 99%

Predicting Application Performance for Multi-vendor Clouds Using Dwarf Benchmarks

Engen

Papay

Phillips

et al. 2012

Web Information Systems Engineering - WISE 2012

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Abstract. Future Internet applications are becoming increasingly dynamic and can be composed of a wide range of services controlled and hosted by di erent stakeholders. This paper addresses the challenge of resource provisioning for applications that have speci c Quality of Service (QoS) requirements and where consumers of Cloud resources want to avoid lock-in to any speci c Infrastructure-as-a-Service (IaaS) provider. Application modelling can be used to predict performance of applications given certain resources, workload and con guration. However, application modelling is a signi cant challenge for Cloud consumers due to the limited and varying information IaaS providers disclose about infrastructure resources. We demonstrate in this paper how Dwarf benchmarks can be used as a uniform and informative way of characterising compute resources, which is successful for application modelling, achieving high prediction accuracy on a range of applications.

show abstract

“…However, the complexity of determining Quality of Service (QoS) requirements for applications in such environments introduces signicant market ineciencies and has driven the emergence of service engineering tools for modelling, analysing and planning the QoS of service based applications deployed within the Cloud [1,2].…”

Section: Introductionmentioning

confidence: 99%

Web Information Systems Engineering - WISE 2012

Wang¹,

Cruz²,

Delis³

et al. 2012

Lecture Notes in Computer Science

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Abstract. Future Internet applications are becoming increasingly dynamic and can be composed of a wide range of services controlled and hosted by dierent stakeholders. This paper addresses the challenge of resource provisioning for applications that have specic Quality of Service (QoS) requirements and where consumers of Cloud resources want to avoid lock-in to any specic Infrastructure-as-a-Service (IaaS) provider. Application modelling can be used to predict performance of applications given certain resources, workload and conguration. However, application modelling is a signicant challenge for Cloud consumers due to the limited and varying information IaaS providers disclose about infrastructure resources. We demonstrate in this paper how Dwarf benchmarks can be used as a uniform and informative way of characterising compute resources, which is successful for application modelling, achieving high prediction accuracy on a range of applications.

show abstract

Virtualised e-Learning with real-time guarantees on the IRMOS platform

Cited by 24 publications

References 20 publications

End-to-End Service Quality for Cloud Applications

End-to-End Service Quality for Cloud Applications

Predicting Application Performance for Multi-vendor Clouds Using Dwarf Benchmarks

Web Information Systems Engineering - WISE 2012

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