Dynamic Provisioning of Virtual Organization Clusters

Murphy, Michael A.; Kagey, Brandon; Fenn, Michael; Goasguen, Sebastien

doi:10.1109/ccgrid.2009.37

Cited by 46 publications

(29 citation statements)

References 12 publications

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“…Virtual Organization Clusters (VOCs), designed around the Virtual Organization Cluster Model (VOC Model) [1], provide a mechanism for the autonomic creation of cloud systems for Virtual Organizations [2], utilizing commodity Grid computing resources as underlying physical hosts for virtual systems. VOCs provision themselves and adapt to changing resource demands within the cloud by automatically leasing physical systems to run VO-customized virtual machines [3]. These dynamic environments are ideally suited to computationally-bound jobs, such as bag-of-tasks applications [4], since the communications overheads introduced by current virtualization technologies can be significant [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…The purpose of this paper is to extend the existing Virtual Organization Cluster dynamic provisioning system [3] to enable private overlay scheduling within a virtual cluster, where the virtual machines comprising the virtual cluster are themselves scheduled on leased physical resources. Through the addition of the IPOP overlay network [9], VOCs can span different administrative domains, allowing physical resources to be leased from different providers and joined into a single cluster.…”

Section: Introductionmentioning

confidence: 99%

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Autonomic Clouds on the Grid

et al. 2010

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Autonomic Clouds on the Grid

et al. 2010

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“…Also, DEVAs have similitudes with virtual clusters such as [9] or [10]. Differently than in our work, these solutions focus on instantiating the required virtual resources and providing the appropriate software and network configuration.…”

Section: Use Of Heterogeneous Devas and Resourcesmentioning

confidence: 99%

DEVA: Distributed Ensembles of Virtual Appliances in the Cloud

Villegas

Sadjadi

2011

Euro-Par 2011 Parallel Processing

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Abstract. Low upfront costs, rapid deployment of infrastructure and flexible management of resources has resulted in the quick adoption of cloud computing. Nowadays, different types of applications in areas such as enterprise web, virtual labs and high-performance computing are already being deployed in private and public clouds. However, one of the remaining challenges is how to allow users to specify Quality of Service (QoS) requirements for composite groups of virtual machines and enforce them effectively across the deployed resources. In this paper, we propose an Infrastructure as a Service resource manager capable of allocating Distributed Ensembles of Virtual Appliances (DEVAs) in the Cloud. DEVAs are groups of virtual machines and their network connectivities instantiated on heterogeneous shared resources with QoS specifications for individual entities as well as their connections. We discuss the different stages in their lifecycle: declaration, scheduling, provisioning and dynamic management, and show how this approach can be used to maintain QoS for complex deployments of virtual resources.

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“…Constraint (2) ensures that the allocated jobs in each VM cannot exceed the running VMs' capacity. Constraint (3) ensures that the allocated jobs in each to-be-provisioned VM can not exceed the VM's capacity. Constraint (4) ensures that each job is only allocated to one VM.…”

Section: Formalization Of the Scheduling Problemmentioning

confidence: 99%

“…Academia [1][2][3][4][5][6][7] and industry [8] are both increasingly using cloud resources as infrastructure to serve their users, due to the elastic, flexible, and pay-as-you-go features of Infrastructureas-a-Service (IaaS) clouds. Cloud brokers need to lease resources from IaaS clouds cheaply, yet execute the users' jobs in time.…”

Section: Introductionmentioning

confidence: 99%

Scheduling Jobs in the Cloud Using On-Demand and Reserved Instances

Shen

Deng

Iosup

et al. 2013

Euro-Par 2013 Parallel Processing

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Abstract. Deploying applications in leased cloud infrastructure is increasingly considered by a variety of business and service integrators. However, the challenge of selecting the leasing strategy -larger or faster instances? on-demand or reserved instances? etc.-and to configure the leasing strategy with appropriate scheduling policies is still daunting for the (potential) cloud user. In this work, we investigate leasing strategies and their policies from a broker's perspective. We propose, CoH, a family of Cloud-based, online Hybrid scheduling policies that minimizes rental cost by making use of both on-demand and reserved instances. We formulate the resource provisioning and job allocation policies as Integer Programming problems. As the policies need to be executed online, we limit the time to explore the optimal solution of the integer program, and compare the obtained solution with various heuristics-based policies; then automatically pick the best one. We show, via simulation and using multiple real-world traces, that the hybrid leasing policy can obtain significantly lower cost than typical heuristics-based policies.

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Dynamic Provisioning of Virtual Organization Clusters

Cited by 46 publications

References 12 publications

Autonomic Clouds on the Grid

Autonomic Clouds on the Grid

DEVA: Distributed Ensembles of Virtual Appliances in the Cloud

Scheduling Jobs in the Cloud Using On-Demand and Reserved Instances

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