Efficient Distribution of Virtual Machines for Cloud Computing

Schmidt, Matthias; Fallenbeck, Niels; Smith, Matthew; Freisleben, Bernd

doi:10.1109/pdp.2010.39

Cited by 60 publications

(51 citation statements)

References 10 publications

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“…Schmidt et al use Unionfs [18], a sophisticated, layered file system along with multicasting to minimize network transfer times of VMIs. VDN [14] is a network hierarchyaware system for transferring VMIs to compute nodes in units of small chunks that can be retrieved from local neighbors.…”

Section: Efficient Vmi Transfermentioning

confidence: 99%

Reducing VM Startup Time and Storage Costs by VM Image Content Consolidation

Razavi

Razorea

Kielmann

2014

Euro-Par 2013: Parallel Processing Workshops

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Abstract. Elastic cloud applications rely on fast virtual machine (VM) startup, e.g. when scaling out for handling increased workload. While there have been recent studies into the VM startup time in clouds, the effects of the VM image (VMI) disk size and its contents are little understood. To fill this gap, we present a detailed study of these factors on Amazon EC2. Based on our findings, we developed a novel approach for consolidating size and contents of VMIs. We then evaluated our approach with the ConPaaS VMI, an open-source Platform-as-a-Service runtime. Compared to an unmodified ConPaaS VMI, our approach results in up to four times reduction of the disk size, three times speedup for the VM startup time, and three times reduction of storage cost.

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Section: Efficient Vmi Transfermentioning

confidence: 99%

Reducing VM Startup Time and Storage Costs by VM Image Content Consolidation

Razavi

Razorea

Kielmann

2014

Euro-Par 2013: Parallel Processing Workshops

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“…However, the broadcast step has an high overhead both in execution time and network traffic, which reduces the attractiveness of IaaS for short-lived jobs and is expensive for the provider (in terms of lost resources that could otherwise be charged for). Thus, reducing the broadcast overhead has been an active area of study, with proposals ranging from multi-cast [9] and application level broadcast-trees [10] to peer-to-peer protocols [11,4].…”

Section: Related Workmentioning

confidence: 99%

Leveraging Collaborative Content Exchange for On-Demand VM Multi-deployments in IaaS Clouds

Nicolae

Rafique

2013

Euro-Par 2013 Parallel Processing

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Abstract. A critical feature of IaaS cloud computing is the ability to deploy, boot and terminate large groups of inter-dependent VMs very quickly, which enables users to efficiently exploit the on-demand nature and elasticity of clouds even for large-scale deployments. A common pattern in this context is multi-deployment, i.e., using the same VM image template to instantiate a large number of VMs in parallel. A difficult trade-off arises in this context: access the content of the template on-demand but slowly due to I/O bottlenecks or pre-broadcast the full contents of the template on the local storage of the hosting nodes to avoid such bottlenecks. Unlike previous approaches that are biased towards either of the extremes, we propose a scheme that augments on-demand access through a collaborative scheme in which the VMs aim to leverage the similarity of access pattern in order to anticipate future accesses and exchange chunks between themselves in an attempt to reduce contention to the remote storage where the VM image template is stored. Large scale experiments show improvements in read throughput between 30%-40% compared to on-demand access schemes that perform in isolation.

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“…Schmidt et al [9] investigate different strategies for distributing virtual machine images within a data center: unicast, multicast, binary tree distribution and peer-to-peer distribution based on BitTorrent. They found the multicast method the most efficient, but in order to be able to distribute images over network boundaries ("cross-cloud") they choose BitTorrent.…”

Section: Related Workmentioning

confidence: 99%

Integrated Monitoring Approach for Seamless Service Provisioning in Federated Clouds

Kertész

Kecskeméti

Marosi

et al. 2012

2012 20th Euromicro International Conference on Parallel, Distributed and Network-Based Processing

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Abstract-Cloud Computing offers simple and cost effective outsourcing in dynamic service environments, and allows the construction of service-based applications using virtualization. By aggregating the capabilities of various IaaS cloud providers, federated clouds can be built. Managing such a distributed, heterogeneous environment requires sophisticated interoperation of adaptive coordinating components. In this paper we introduce an integrated federated management and monitoring approach that enables autonomous service provisioning in federated clouds. In this architecture, cloud brokers manage the number and the location of the utilized virtual machines for the received service requests. In order to provide seamless service executions, a state of the art monitoring solution is proposed that supports cloud selection performed by the management layer of the architecture. Our solution is able to cope with highly dynamic service executions by federating heterogeneous cloud infrastructures in a transparent and autonomous manner.

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Efficient Distribution of Virtual Machines for Cloud Computing

Cited by 60 publications

References 10 publications

Reducing VM Startup Time and Storage Costs by VM Image Content Consolidation

Reducing VM Startup Time and Storage Costs by VM Image Content Consolidation

Leveraging Collaborative Content Exchange for On-Demand VM Multi-deployments in IaaS Clouds

Integrated Monitoring Approach for Seamless Service Provisioning in Federated Clouds

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