Introducing Risk Management into the Grid

Djemame, Karim; Gourlay,; Padgett, James; Birkenheuer,; Hovestadt, Thomas; Kao,; Voss,

doi:10.1109/e-science.2006.261112

Cited by 26 publications

(25 citation statements)

References 20 publications

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“…The AssessGrid project [23] proposes a model to estimate the probability of SLA failures in Grid environments, and considers the probability of n resources failing for the scheduled duration of a task as well as the probability that m reserved resources are available for that duration. The probability of node failure is calculated by assuming that the node failures represent a Poisson process, which is non-homogenous in time.…”

Section: Related Workmentioning

confidence: 99%

A Risk Assessment Framework for Cloud Computing

Djemame

Armstrong

Guitart

et al. 2016

IEEE Trans. Cloud Comput.

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Abstract-Cloud service providers offer access to their resources through formal Service Level Agreements (SLA), and need wellbalanced infrastructures so that they can maximise the Quality of Service (QoS) they offer and minimise the number of SLA violations. This paper focuses on a specific aspect of risk assesment as applied in cloud computing: methods within a framework that can be used by cloud service providers and service consumers to assess risk during service deployment and operation. It describes the various stages in the service lifecycle wheres risk assessment takes place, and the corresponding risk models that have been designed and implemented. The impact of risk on architectural components, with special emphasis on holistic management support at service operation, is also described. The risk assessor is shown to be effective through the experimental evaluation of the implementation, and is already integrated in a cloud computing toolkit.

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Section: Related Workmentioning

confidence: 99%

A Risk Assessment Framework for Cloud Computing

Djemame

Armstrong

Guitart

et al. 2016

IEEE Trans. Cloud Comput.

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“…QoS can also be achieved by introducing risk management into the Grid, which is elaborated in [5]. Their proposal allows modeling and managing the risk that the service level agreement (SLA) cannot be fulfilled.…”

Section: Related Workmentioning

confidence: 99%

Extended Resource Management Using Client Classification and Economic Enhancements

Püschel

Borissov

Neumann

et al. 2009

Economic Models and Algorithms for Distributed Systems

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Commercialization of Grid resources will become more and more important as utility computing and the deployment of Grids gains momentum. This results in the necessity to not only base Grid components on technical aspects, but also to include economical aspects in their design. This paper presents a framework that links technical and economical aspects to the management of computational resources. Economic enhancements like dynamic pricing and client classification are introduced based on a technical resource management environment and positioned within this resulting in a proposed architecture for an Economically Enhanced Resource Manager (EERM). The introduced approach is evaluated considering various economic design criteria and example scenarios.

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“…Risk assessment in distributed computing has been researched in various projects, which have included objectives ranging from information protection, evaluation/prediction of QoS and probability of SLA failures [8], [9], [10].…”

Section: Related Workmentioning

confidence: 99%

Risk-Driven Proactive Fault-Tolerant Operation of IaaS Providers

Guitart

Macías

Djemame

et al. 2013

2013 IEEE 5th International Conference on Cloud Computing Technology and Science

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Abstract-In order to improve service execution in Clouds, the management of Cloud Infrastructure has to take measures to adhere to Service Level Agreements and Business Level Objectives, from the application layer through to how services are supported at the lowest hardware levels. In this paper a risk model methodology and holistic management approach is developed specific to the operation of the Cloud Infrastructure Provider and is applied through improvements to SLA fault tolerance in Cloud Infrastructure. Risk assessments are used to analyse execution specific data from the Cloud Infrastructure and linked to a business driven holistic management component that is part of a Cloud Manager. Initial results show improved ecoefficiency, virtual machine availability and reductions in SLA failure across the whole Cloud infrastructure by applying our combined risk-based fault tolerance approach.

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Introducing Risk Management into the Grid

Abstract: Service Level Agreements (SLAs)

Cited by 26 publications

References 20 publications

A Risk Assessment Framework for Cloud Computing

A Risk Assessment Framework for Cloud Computing

Extended Resource Management Using Client Classification and Economic Enhancements

Risk-Driven Proactive Fault-Tolerant Operation of IaaS Providers

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