Elastic Site: Using Clouds to Elastically Extend Site Resources

Marshall, Paul; Keahey, Kate; Freeman, Tim

doi:10.1109/ccgrid.2010.80

Cited by 221 publications

(136 citation statements)

References 12 publications

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“…Marshall et al proposed an IaaS cloud solution to elastically extend physical clusters with cloud resources [6]. They created a so-called elastic site manager on top of Nimbus, which interfaces directly with local cluster managers and three different policies were examined for elastic site addition.…”

Section: Related Workmentioning

confidence: 99%

Strategies for Increased Energy Awareness in Cloud Federations

Kecskeméti

Kertész

Marosi

et al. 2014

High‐Performance Computing on Complex Environments

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Section: Related Workmentioning

confidence: 99%

Strategies for Increased Energy Awareness in Cloud Federations

Kecskeméti

Kertész

Marosi

et al. 2014

High‐Performance Computing on Complex Environments

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“…Closest to our work, our own [8,16,17] and related [44][45][46]5] studies of multiple scheduling policies have emphasized the inability of any single policy to perform well under a wide yet realistic variety of scientific workloads.…”

Section: Related Workmentioning

confidence: 99%

A Periodic Portfolio Scheduler for Scientific Computing in the Data Center

Deng

Verboon

Ren

et al. 2014

Job Scheduling Strategies for Parallel Processing

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Abstract. The popularity of data centers in scientific computing has led to new architectures, new workload structures, and growing customerbases. As a consequence, the selection of efficient scheduling algorithms for the data center is an increasingly costlier and more difficult challenge. To address this challenge, and contrasting previous work on scheduling for scientific workloads, we focus in this work on portfolio schedulinghere, the dynamic selection and use of a scheduling policy, depending on the current system and workload conditions, from a portfolio of multiple policies. We design a periodic portfolio scheduler for the workload of the entire data center, and equip it with a portfolio of resource provisioning and allocation policies. Through simulation based on real and synthetic workload traces, we show evidence that portfolio scheduling can automatically select the scheduling policy to match both user and data center objectives, and that portfolio scheduling can perform well in the data center, relative to its constituent policies.

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“…In the context of hybrid cloud, de Assuncao et al [26] investigate whether an organization operating its local cluster can benefit from using cloud providers to improve the performance of its users' requests; Marshall et al 's evaluation of elastic site [25] consists primarily of a comparison of the three different policies (on demand, steady stream, and bursts) in an attempt to maximize job turnaround time while minimizing thrashing and idle VMs. Palankar et al [29] evaluates S3 as a black box and reasons whether S3 is an appropriate service for science grids.…”

Section: Evaluation Of Cloud Systemsmentioning

confidence: 99%

“…In the context of hybrid cloud, recently, Sun Microsystems has added support for Amazon EC2 into Sun Grid Engine (SGE); Moreno-Vozmediano et al [22] analyze the deployment of generic clustered services on top of a virtualized infrastructure layer that combines a VM manager (on a local cluster) and a cloud resource provider (external cloud provider: Amazon EC2). Marshall et al [25] have implemented a resource manager, built on the Nimbus toolkit to dynamically and securely extend existing physical clusters into the cloud. Rodero-Merino et al [39] proposes a new abstraction layer that allows for their automatic deployment and escalation depending on the service status.…”

Section: Infrastructure For Scientific Communitiesmentioning

confidence: 99%

“…In scientific communities, more and more research groups show great interests in utilizing open source cloud computing tools to build private clouds [19] [28] [34], or proposing hybrid cloud models [22] [25] [26] to augment their local computing resources with external public clouds. In this paper, we take a different perspective to focus on public clouds, and intend to answer one key question: in public cloud, can small-to-medium scale scientific communities benefit from the economies of scale?…”

Section: Introductionmentioning

confidence: 99%

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In Cloud, Can Scientific Communities Benefit from the Economies of Scale?

Wang

Zhan

Shi

et al. 2012

IEEE Trans. Parallel Distrib. Syst.

102

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Abstract-The basic idea behind cloud computing is that resource providers offer elastic resources to end users. In this paper, we intend to answer one key question to the success of cloud computing: in cloud, can small-to-medium scale scientific communities benefit from the economies of scale? Our research contributions are three-fold: first, we propose an innovative public cloud usage model for small-to-medium scale scientific communities to utilize elastic resources on a public cloud site while maintaining their flexible system controls, i.e., create, activate, suspend, resume, deactivate, and destroy their high-level management entities-service management layers without knowing the details of management. Second, we design and implement an innovative system-DawningCloud, at the core of which are lightweight service management layers running on top of a common management service framework. The common management service framework of DawningCloud not only facilitates building lightweight service management layers for heterogeneous workloads, but also makes their management tasks simple. Third, we evaluate the systems comprehensively using both emulation and real experiments. We found that for four traces of two typical scientific workloads: high throughput computing (HTC) and many task computing (MTC), DawningCloud saves the resource consumption maximally by 59.5% and 72.6% for HTC and MTC service providers, respectively, and saves the total resource consumption maximally by 54% for the resource provider with respect to the previous two public cloud solutions. To this end, we conclude that small-to-medium scale scientific communities indeed can benefit from the economies of scale of public clouds with the support of the enabling system.

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Elastic Site: Using Clouds to Elastically Extend Site Resources

Cited by 221 publications

References 12 publications

Strategies for Increased Energy Awareness in Cloud Federations

Strategies for Increased Energy Awareness in Cloud Federations

A Periodic Portfolio Scheduler for Scientific Computing in the Data Center

In Cloud, Can Scientific Communities Benefit from the Economies of Scale?

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