Ontology-Driven Composition and Validation of Scientific Grid Workflows in Kepler: a Case Study of Hyperspectral Image Processing

Zhang, Jianting

doi:10.1109/gccw.2006.68

Cited by 19 publications

(8 citation statements)

References 29 publications

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“…1, we list the key interfaces in Table III, and point out the implementation status and interaction relationships. We will introduce the definitions of some pivotal interfaces in the following, and further details about these interfaces are available at our website 4 .…”

Section: ) Interface Definitionsmentioning

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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Section: ) Interface Definitionsmentioning

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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“…While there are considerable works on automatic composition and verification of Web Services based business workflows (see [15] [16] for introductions and brief surveys), the complex logic tools (such as automata) behind are not intuitive to scientific domain users and their applicability to real scientific Grid computing applications is unclear. In paper [3], the author tries to use ontologies to help reducing semantic problems rather than expect to eliminate above problems completely. Based on this study, a Scientific Grid Workflows in Kepler is designed.…”

Section: Introductionmentioning

confidence: 99%

“…Many Grid workflow languages based on business workflow languages, generic business workflow composition environments may be extended to compose Grid workflows, quite a few Grid workflow languages have been proposed [3], such as Grid Services Flow Language (GSFL, [7]), Grid Application Definition Language (GADL, [8]), Grid Services Workflow Execution Language (GSWEL, [9]), GridAnt [10], Abstract Grid Workflow Language (AGWL, [11] [12]), and so on. However, for the Grid workflow languages that choose to use system specific workflow constructs (e.g., GADL and AGWL), graphic tools are usually provided to facilitate users to visually compose Grid workflows and transform graphic representations into the Grid workflow languages internally, such as UML based tool for AGWL [13] and Grid Job Builder for GADL [14].…”

Section: Introductionmentioning

confidence: 99%

“…The technology that can achieve resource sharing and cooperating in harmony, has been developing into an advanced technology and an important research，increasing popular in E-world, profiting from the developing of WWW science and technology，their infrastructures and academe effort during the past 10 years. Many computation-intensive scientific domains, ranging from astronomy to bioinformatics, have had successful stories in Grid computing by integrating large-scale, distributed and heterogeneous resources [1][2][3][4]. Grid workflow plays an important role in Grid computing, due to the following advantages:…”

Section: Introductionmentioning

confidence: 99%

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A Framework for Designing Grid Workflow System based on Ontology

Pang

Wang

Jiang

2007

Sixth International Conference on Grid and Cooperative Computing (GCC 2007)

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Grid computing is innovative information service infrastructure for dynamic and distributed resources sharing and collaboration. Grid workflow is used to handle tasks with control and data dependencies ， and plays an important role in Grid computing. It is essential to design an appropriate model to satisfy the distributed and heterogeneous workflow systems that must be flexible, reusable, dynamic feature in higher level. As the idea of the designing and composing semantic Web services, a method for designing Grid workflow system framework based on ontology is proposed in this paper. Four types of Ontology concept are defined: Workflow_Meta Ontology, Model_Driven Method Ontology, Knowledge Representation Ontology and Date Types Ontology, and the particular description of their functions, constitutes and relations with each other are given. Based on this framework, the Grid workflow systems will have stronger capability to deal with their cooperation and dynamic composition with each other.

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“…Ontology [16] technologies have been used by the Grid community [24,5,32,17,27,23] for semantic descriptions and discovery of workflow activities. An ontology is a formal representation of a set of concepts within a domain and the relationships among those concepts.…”

Section: Introductionmentioning

confidence: 99%

A novel graph based approach for automatic composition of high quality grid workflows

Qin

Fahringer

Prodan

2009

Proceedings of the 18th ACM International Symposium on High Performance Distributed Computing

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The workflow paradigm is one of the most important programming models for the Grid. The composition of Grid workflows has been widely studied in the Grid community. However, there is still a lack of a general and efficient approach for automatic composition of Grid workflows. In this paper, we present a STRIPS (Stanford Research Institute Problem Solver) based formal definition of the Grid workflow composition problem, followed by a novel graph based algorithm for automatic composition of high quality (portable, fault tolerant and optimized) Grid workflows. Our algorithm searches for semantic descriptions of workflow activities, i.e., Activity Functions (AFs), defined by ontologies and composes them into Grid workflows using AF Data Dependence (ADD) graphs. The composition process consists of three phases: ADD graph creation, workflow extraction, and workflow optimization. The worst case complexity of our algorithm is quadratic in the number of AFs. An extension of our algorithm to compose Grid workflows with branches and loops is also presented. Experimental results illustrate the effectiveness and efficiency of our approach: (i) the measured worst case execution time of our algorithm further proofs the analyzed time complexity; (ii) the composition of the real world meteorology Grid workflow application MeteoAG with our algorithm takes approximate half a second; and (iii) the execution time of the MeteoAG workflow when running on the Austrian Grid is reduced by up to 25% and the speedup is increased by up to 2.24 by applying our workflow optimization techniques.

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Ontology-Driven Composition and Validation of Scientific Grid Workflows in Kepler: a Case Study of Hyperspectral Image Processing

Cited by 19 publications

References 29 publications

Devising a Cloud Scientific Workflow Platform for Big Data

Devising a Cloud Scientific Workflow Platform for Big Data

A Framework for Designing Grid Workflow System based on Ontology

A novel graph based approach for automatic composition of high quality grid workflows

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