Enabling Generic Distributed Computing Infrastructure Compatibility for Workflow Management Systems

Kozlovszky, Miklós; Karóczkai, Krisztián; Márton, István; Balaskó, Ákos; Marosi, Attila Csaba; Kacsuk, Péter

doi:10.7494/csci.2012.13.3.61

Cited by 17 publications

(8 citation statements)

References 9 publications

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“…The series of works [14] [16] presented a brokerbased framework to support the execution of workflow applications on a multi-Cloud environment.…”

Section: Related Workmentioning

confidence: 99%

Devising a Cloud Scientific Workflow Platform for Big Data

Zhao

et al. 2014

2014 IEEE World Congress on Services

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Abstract-Scientificworkflow management systems (SWFMSs) are facing unprecedented challenges from big data deluge. As revising all the existing workflow applications to fit into Cloud computing paradigm is impractical, thus migrating SWFMSs into the Cloud to leverage the functionalities of both Cloud computing and SWFMSs may provide a viable approach to big data processing. In this paper, we first discuss the challenges for scientific workflow applications and the available solutions in details, and analyze the essential requirements for a scientific computing Cloud platform. Then we propose a service framework to normalize the integration of SWFMS with Cloud computing. Meanwhile, we also present our implementation experience based on the service Framework. At last, we set up a series of experiments to demonstrate the capability of our implementation and use a Montage Image Mosaic Workflow as a showcase of the implementation.

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“…The series of works [14] [16] presented a brokerbased framework to support the execution of workflow applications on a multi-Cloud environment.…”

Section: Related Workmentioning

confidence: 99%

Devising a Cloud Scientific Workflow Platform for Big Data

Zhao

et al. 2014

2014 IEEE World Congress on Services

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“…The series of works [5] [19] presented a brokerbased framework to support the execution of workflow applications on a multi-Cloud environment. Bhaskar Prasad Rimal et al [4] discussed a framework of scientific workflow for multi-tenant cloud orchestration environment that deals with semantic-based workflow as well as policy-based workflow.…”

Section: Related Workmentioning

confidence: 99%

Architecting Cloud Workflow: Theory and Practice

Zhao

Raicu

et al. 2014

2014 IEEE International Conference on Computer and Information Technology

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Abstract-The data scale, science analysis and processing complexity in scientific community are growing exponentially in the "big data" era. Cloud computing paradigm has been widely adopted to provide unprecedented scalability and resources on demand, while scientific workflow management systems (SWFMSs) have been proven essential to scientific computing and services computing. Uniting the advantages of both cloud computing and SWFMSs can bring a valuable solution to the scientific "big data" problem to researchers. Although a series of work have concentrated on integrating SWFMSs with Cloud platforms that provide much experience for future research and development, a study from an architectural perspective is still missing. The main contributions of this paper are: 1) based on a comprehensive survey of the available integration options, we propose a service framework for integrating SWFMSs with Cloud computing; 2) we implement the service framework based on various Cloud platforms to validate the feasibility of the proposed framework; and 3) we conduct a set of experiments to demonstrate the capability and use a NASA MODIS image processing workflow as a showcase of the implementation.

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“…Ideally, workflow specifications would be independent of the particular code and software environment, specifying only the domain task to be carried out rather than what application codes to run. Previous work has focused on interoperability of workflow systems and workflow representations [8], but not on creating more abstract representations that address the domain layer.…”

Section: Introductionmentioning

confidence: 99%

Mapping Semantic Workflows to Alternative Workflow Execution Engines

Gil

2013

2013 IEEE Seventh International Conference on Semantic Computing

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Abstract-Current workflows have limited reusability and shelf life because they specify particular application software to be run at each step, which can become obsolete or no longer run. We describe semantic workflow representations composed of domain tasks, which the system then automatically maps to the application codes available in the particular execution environment. We have implemented this approach in the WINGS semantic workflow system, and demonstrate the mapping of workflows to different sets of application codes depending on the workflow execution engine and execution environment selected.

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Enabling Generic Distributed Computing Infrastructure Compatibility for Workflow Management Systems

Cited by 17 publications

References 9 publications

Devising a Cloud Scientific Workflow Platform for Big Data

Devising a Cloud Scientific Workflow Platform for Big Data

Architecting Cloud Workflow: Theory and Practice

Mapping Semantic Workflows to Alternative Workflow Execution Engines

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