HAND: Highly Available Dynamic Deployment Infrastructure for Globus Toolkit 4

Li, Qi; Jin, Hai; Foster, Ian; Gawor, Jarek

doi:10.1109/pdp.2007.49

Cited by 45 publications

(22 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Container based systems (e.g. [7,24]) predefine an execution platform for the services that includes the deployment system. Therefore services have to be developed for this specific platform and they are not portable between the different container based deployment systems.…”

Section: Service Deployment Overviewmentioning

confidence: 99%

“…HAND (Highly Available Dynamic Deployment Infrastructure) [24] supports several approaches for deployment and provides two deployment solutions called HAND-C (container level solution that requires the container to be restarted after a service injection), and HAND-S (a service level solution that leaves all other services unaffected during deployment). Between HAND and HDS the only difference that HAND supports the latest Globus Web Services Resource Framework (WSRF - [3]) container and offers container and service level deployment.…”

Section: Related Workmentioning

confidence: 99%

“…srv. [29] Container -√ √ -HAND [24] Container -√ √ -WSPeers [14] Container -√ √ -Dynagrid [7] Container - ware components. The other implementations only implement selected standards of the CDDLM.…”

Section: Isolationmentioning

confidence: 99%

See 2 more Smart Citations

An approach for virtual appliance distribution for service deployment

Kecskeméti

Terstyánszky

Kacsuk

et al. 2011

Future Generation Computer Systems

View full text Add to dashboard Cite

Fulfilling a service request in highly dynamic service environments may require deploying a service. Therefore, the effectiveness of service deployment systems affects initial service response times. On Infrastructure as a Service (IaaS) cloud systems deployable services are encapsulated in virtual appliances. Services are deployed by instantiating virtual machines with their virtual appliances. The virtual machine instantiation process is highly dependent on the size and availability of the virtual appliance that is maintained by service developers. This article proposes an automated virtual appliance creation service that aids the service developers to create efficiently deployable virtual appliances -in former systems this task was carried out manually by the developer. We present an algorithm that decomposes these appliances in order to replicate the common virtual appliance parts in IaaS systems. These parts are used to reduce the deployment time of the service by rebuilding the virtual appliance of the service on the deployment target site. With the prototype implementation of the proposed algorithms we demonstrate the decomposition and appliance rebuilding algorithms on a complex web service.

show abstract

Section: Service Deployment Overviewmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

An approach for virtual appliance distribution for service deployment

Kecskeméti

Terstyánszky

Kacsuk

et al. 2011

Future Generation Computer Systems

View full text Add to dashboard Cite

show abstract

“…A grid is a geographically distributed computation infrastructure composed of a set of heterogeneous machines, often with separate policies for security and resource use (Qi et al [18]), that users can access via a single interface. Grids therefore, provide a common resource-access technology and operational services across widely distributed virtual organizations composed of institutions or individuals that share resources.…”

Section: Grid Environmentmentioning

confidence: 99%

Text mining on a grid environment

2009

View full text Add to dashboard Cite

The enormous amount of information stored in unstructured texts cannot simply be used for further processing by computers, which typically handle text as simple sequences of character strings. Text mining is the process of extracting interesting information and knowledge from unstructured text. One key difficulty with text classification learning algorithms is that they require many hand-labeled documents to learn accurately. In the text mining pattern discovery phase, the text classification step aims to automatically attribute one or more pre-defined classes to text documents. In this research, we propose to use an algorithm for learning from labeled and unlabeled documents based on the combination of Expectation-Maximization (EM) and a naïve Bayes classifier on a grid environment, this combination is based on a mixture of multinomials, which is commonly used in text classification. Naïve Bayes is a probabilistic approach to inductive learning. It estimates the a posteriori probability that a document belongs to a class given the observed feature values of the document, assuming independence of the features. The class with the maximum a posteriori probability is assigned to the document. EM is a class of iterative algorithms for maximum likelihood or maximum a posteriori estimation in problems with unlabeled data. The grid environment is a geographically distributed computation infrastructure composed of a set of heterogeneous resources. Text classification mining methods are time-consuming, but using the grid infrastructure can bring significant benefits in the learning and classification process.

show abstract

“…A grid is an internet-connected computing environment in which computing and data resources are geographically distributed over different administrative domains, often with separate policies for security and use of resources [9]. Two distinct computational grid environments are used in this work: the NACAD Grid, installed at the NACAD laboratory, and the EELA Grid.…”

Section: Grid Environmentsmentioning

confidence: 99%

Text Mining Grid Services for Multiple Environments

Serpa

Roncero

Costa

et al. 2008

High Performance Computing for Computational Science - VECPAR 2008

View full text Add to dashboard Cite

Abstract. The objective of this paper is to describe the implementation of text mining grid services for Aîuri Project, which is a framework that includes a friendly user interface, data and text mining tasks, database access and a visualization tool integrated with various grid environments. The focus is the development and test of components for analysis and evaluation of unstructured data into distinct grid environments. These components will be grid services for text mining processes using several approaches of execution, depending on which grid environment the user choose to submit.All components are open source and are freely available to the scientific community, providing access to existing services as well as encouraging the addition of new ones.

show abstract

HAND: Highly Available Dynamic Deployment Infrastructure for Globus Toolkit 4

Abstract: Abstract-Grid

Cited by 45 publications

References 19 publications

An approach for virtual appliance distribution for service deployment

An approach for virtual appliance distribution for service deployment

Text mining on a grid environment

Text Mining Grid Services for Multiple Environments

Contact Info

Product

Resources

About