A Negotiation Mechanism for Advance Resource Reservations Using the Alternate Offers Protocol

Venugopal, Srikumar; Chu, Xingchen; Buyya, Rajkumar

doi:10.1109/iwqos.2008.10

Cited by 80 publications

(41 citation statements)

References 20 publications

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“…The traces have no information about the applications deadlines. We used the method presented in [29] to generate synthetically the deadlines for the needs of our experiments. The applications are classified into two classes named High Urgency (HU) and Low Urgency (LU).…”

Section: Experimental Settingsmentioning

confidence: 99%

A Pareto-based metaheuristic for scheduling HPC applications on a geographically distributed cloud federation

2012

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Section: Experimental Settingsmentioning

confidence: 99%

A Pareto-based metaheuristic for scheduling HPC applications on a geographically distributed cloud federation

2012

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“…The traces do not have information about the applications deadlines. We inspired our self from the method presented in [16] to generate synthetically the deadlines for the needs of our experimentations. The applications were classified into two classes named High Urgency (HU) and Low Urgency (LU).…”

Section: Experimental Settingsmentioning

confidence: 99%

A pareto-based GA for scheduling HPC applications on distributed cloud infrastructures

Kessaci

Melab

Talbi

2011

2011 International Conference on High Performance Computing &Amp; Simulation

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“…In order to initiate a negotiation, GSI [7] security is required. The negotiation is performed based on the alternate offers protocol [32]. Therefore, the workflow application understands only the alternate offers protocol, and negotiation with resources which do not provide alternate offers protocol cannot be properly accomplished.…”

Section: Case Studymentioning

confidence: 99%

An SLA-based resource virtualization approach for on-demand service provision

Kertész

Kecskeméti

Brandić

2009

Proceedings of the 3rd International Workshop on Virtualization Technologies in Distributed Computing

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Cloud computing is a newly emerged research infrastructure that builds on the latest achievements of diverse research areas, such as Grid computing, Service-oriented computing, business processes and virtualization. In this paper we present an architecture for SLA-based resource virtualization that provides an extensive solution for executing user applications in Clouds. This work represents the first attempt to combine SLA-based resource negotiations with virtualized resources in terms of on-demand service provision resulting in a holistic virtualization approach. The architecture description focuses on three topics: agreement negotiation, service brokering and deployment using virtualization. The contribution is also demonstrated with a real-world case study.

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A Negotiation Mechanism for Advance Resource Reservations Using the Alternate Offers Protocol

Cited by 80 publications

References 20 publications

A Pareto-based metaheuristic for scheduling HPC applications on a geographically distributed cloud federation

A Pareto-based metaheuristic for scheduling HPC applications on a geographically distributed cloud federation

A pareto-based GA for scheduling HPC applications on distributed cloud infrastructures

An SLA-based resource virtualization approach for on-demand service provision

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