Advertisement

Automatic Scientific Workflow Composition

  • Jun Qin
  • Thomas Fahringer
Chapter

Abstract

Although the composition of scientific workflows has been widely studied, there is still a lack of a general and efficient approach for automatic composition of scientific workflows. In this chapter, we present a STRIPS-based formal definition of the scientific workflow composition problem, followed by an algorithm for automatic composition of high quality (portable, fault tolerant, and optimized) scientific workflows. The algorithm consists of two sub-algorithms dealing with control and data flow composition, respectively. The automatic control flow composition algorithm searches for Activity Function (AFs) and automatically composes them into scientific workflows using an AF Data Dependence (ADD) graph. The composition process consists of three phases: ADD graph creation, workflow extraction, and workflow optimization. The worst case complexity of the algorithm is quadratic in the number of AFs. An extension of the algorithm to compose scientific workflows with branches and loops is also presented. Once control flow is established, the data flow composition algorithm composes data flow of scientific workflows by locating possible source data ports of each sink data port through backwards control flow traversing, and matching source data ports against sink data ports based on data semantics.

Keywords

Execution Time Goal State Total Execution Time Data Port Automatic Composition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Martin Alt, Sergei Gorlatch, Andreas Hoheisel, and Hans-Werner Pohl. A Grid Workflow Language Using High-Level Petri Nets. Technical Report CoreGRID TR-0032, Institute on Grid Information, Resource and Workflow Monitoring Services, March 2006.Google Scholar
  2. 2.
    Ilkay Altintas, Chad Berkley, Efrat Jaeger, Matthew Jones, Bertram Ludäscher, and Steve Mock. Kepler: An Extensible System for Design and Execution of Scientific Workflows. In 16th Intl. Conf. on Scientific and Statistical Database Management (SSDBM’04), Santorini Island, Greece, June 21–23, 2004. IEEE Computer Society Press.Google Scholar
  3. 3.
    Ilkay Altintas, Adam Birnbaum, Kim K. Baldridge, Wibke Sudholt, Mark Miller, Celine Amoreira, Yohann Potier, and Bertram Ludäscher. A Framework for the Design and Reuse of Grid Workflows. In Proceedings of Scientific Applications of Grid Computing, 2005.Google Scholar
  4. 4.
    José Luis Ambite and Dipsy Kapoor. Automatically Composing Data Workflows with Relational Descriptions and Shim Services. In Proceedings of 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference (ISWC 2007 + ASWC 2007), Busan, Korea, November 2007. Springer Berlin / Heidelberg.Google Scholar
  5. 5.
    José Luis Ambite and Matthew Weathers. Automatic Composition of Aggregation Workflows for Transportation Modeling. In Proceedings of the National Conference on Digital Government Research (dg.o2005), pages 41–49. Digital Government Society of North America, 2005.Google Scholar
  6. 6.
    Tony Andrews, Francisco Curbera, Hitesh Dholakia, Yaron Goland, Johannes Klein, Frank Leymann, Kevin Liu, Dieter Roller, Doug Smith, Satish Thatte, Ivana Trickovic, and Sanjiva Weerawarana. Business Process Execution Language for Web Services Version 1.1. http://download.boulder.ibm.com/ibmdl/pub/software/dw/specs/ws-bpel/ws-bpel.pdf, May 2003.
  7. 7.
    James Annis, Yong Zhao, Jens Voeckler, Michael Wilde, Steve Kent, and Ian Foster. Applying Chimera Virtual Data Concepts to Cluster Finding in the Sloan Sky Survey. In Supercomputing ’02: Proceedings of the 2002 ACM/IEEE conference on Supercomputing, pages 1–14, Los Alamitos, CA, USA, 2002. IEEE Computer Society Press.Google Scholar
  8. 8.
    Grigoris Antoniou and Frank van Harmelen. Web Ontology Language: OWL. In S. Staab and R. Studer, editors, Handbook on Ontologies in Information Systems, pages 76–92. Springer-Verlag, 2003.Google Scholar
  9. 9.
    C. Archer. Process Coordination and Ubiquitous Computing. CRC Press, Inc., Boca Raton, FL, USA, 2002.Google Scholar
  10. 10.
    Rob Armstrong, Gary Kumfert, Lois Curfman McInnes, Steven Parker, Ben Allan, Matt Sottile, Thomas Epperly, and Tamara Dahlgren. The CCA Component Model For High-Performance Scientific Computing. Concurrency and Computation: Practice & Experience, 18(2):215–229, 2006.Google Scholar
  11. 11.
    ASG Team. Adaptive Services Grid (ASG). http://asg-platform.org.
  12. 12.
    Austrian Grid Team. The Austrian Grid Project. http://www.austriangrid.at, 2006.
  13. 13.
    P. Avery and Ian Foster. GriPhyN Annual Report for 2003–2004. Technical Report 2004–70, August 2004.Google Scholar
  14. 14.
    Laurent Baduel, Françoise Baude, Denis Caromel, Arnaud Contes, Fabrice Huet, Matthieu Morel, and Romain Quilici. Grid Computing: Software Environments and Tools, chapter Programming, Deploying, Composing, for the Grid. Springer-Verlag, January 2006.Google Scholar
  15. 15.
    Emir M. Bahsi, Emrah Ceyhan, and Tevfik Kosar. Conditional Workflow Management: a Survey and Analysis. Scientific Programming, 15(4):283–297, 2007.Google Scholar
  16. 16.
    Mark Baker and Bryan Carpenter. MPJ: A Proposed Java Message Passing API and Environment for High Performance Computing. In IPDPS ’00: Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing, pages 552–559, London, UK, 2000. Springer-Verlag.Google Scholar
  17. 17.
    Roger Barga and Dennis Gannon. Workflows for e-Science – Scientific Workflows for Grids, chapter Scientific versus Business Workflow, pages 9–16. Springer Verlag, 2007.Google Scholar
  18. 18.
    Charlton Barreto, Vaughn Bullard, Thomas Erl, John Evdemon, Diane Jordan, Khanderao Kand, Dieter König, Simon Moser, Ralph Stout, Ron Ten-Hove, Ivana Trickovic, and Danny van der Rijn Alex Yiu. Web Services Business Process Execution Language Version 2.0 Primer. http://docs.oasis-open.org/wsbpel/2.0/Primer/wsbpel-v2.0-Primer.pdf, May 2007.
  19. 19.
    Ricardo M. Bastos, Duncan Dubugras, and A. Ruiz. Extending UML Activity Diagram for Workflow Modeling in Production Systems. In Proceedings of 35th Annual Hawaii International Conference on System Sciences (HICSS’02), Big Island, Hawaii, January 07–10, 2002. IEEE Computer Society Press.Google Scholar
  20. 20.
    Sean Bechhofer, Frank van Harmelen, Jim Hendler, Ian Horrocks, Deborah L. McGuinness, Peter F. Patel-Schneider, and Lynn Andrea Stein. OWL Web Ontology Language Reference. Technical report, The World Wide Web Consortium (W3C), 2004.Google Scholar
  21. 21.
    Stefano Beco, Barbara Cantalupo, Ludovico Giammarino, Nikolaos Matskanis, and Mike Surridge. OWL-WS: A Workflow Ontology for Dynamic Grid Service Composition. In 1st IEEE International Conference on e-Science and Grid Computing, pages 148–155. IEEE Computer Society, December 5–8, 2005.Google Scholar
  22. 22.
    Khalid Belhajjame, Katy Wolstencroft, Oscar Corcho, Tom Oinn, Franck Tanoh, Alan William, and Carole Goble. Metadata Management in the Taverna Workflow System. In Proceedings of the IEEE International Symposium on Cluster Computing and the Grid (CCGrid), pages 651–656, Los Alamitos, CA, USA, 2008. IEEE Computer Society.Google Scholar
  23. 23.
    Chad Berkley, Shawn Bowers, Matthew Jones, Bertram Ludäscher, Mark Schildhauer, and Jing Tao. Incorporating Semantics in Scientific Workflow Authoring. In SSDBM’2005: Proceedings of the 17th international conference on Scientific and statistical database management, pages 75–78, Berkeley, CA, US, 2005. Lawrence Berkeley Laboratory.Google Scholar
  24. 24.
    Chad Berkley, Shawn Bowers, Matthew Jones, Bertram Ludäscher, Mark Schildhauer, and Jing Tao. Incorporating Semantics in Scientific Workflow Authoring. In SSDBM’2005: Proceedings of the 17th international conference on Scientific and statistical database management, pages 75–78, Berkeley, CA, US, 2005. Lawrence Berkeley Laboratory.Google Scholar
  25. 25.
    Peter Blaha, Karlheinz Schwarz, Georg Madsen, Dieter Kvasnicka, and Joachim Luitz. WIEN2k: An Augmented Plane Wave plus Local Orbitals Program for Calculating Crystal Properties, 2001.Google Scholar
  26. 26.
    Avrim L. Blum and Merrick L. Furst. Fast Planning Through Planning Graph Analysis. Artificial Intelligence, 90:281–300, 1997.Google Scholar
  27. 27.
    Shawn Bowers and Bertram Ludäscher. An Ontology-Driven Framework for Data Transformation in Scientific Workflows. In Proceeding of International Workshop on Data Integration in the Life Sciences (DILS 2004), pages 1–16, 2004.Google Scholar
  28. 28.
    Shawn Bowers and Bertram Ludäscher. Actor-Oriented Design of Scientific Workflows. In 24st Intl. Conference on Conceptual Modeling. Springer, 2005.Google Scholar
  29. 29.
    Jian Cao, Yujie Mou, Jie Wang, Shensheng Zhang, and Minglu Li. A Dynamic Grid Workflow Model Based On Workflow Component Reuse. In Proceedings of Grid and Cooperative Computing - GCC 2005, 2005.Google Scholar
  30. 30.
    Junwei Cao, Stephen A. Jarvis, Subhash Saini, and Graham R. Nudd. GridFlow: Workflow Management for Grid Computing. In 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGrid 2003), Tokyo, Japan, May 12–15, 2003. IEEE Computer Society Press.Google Scholar
  31. 31.
    Jorge Cardoso and Amit Sheth. Semantic E-Workflow Composition. In Journal Of Intelligent Information Systems, volume 21, pages 191–225, Hingham, MA, USA, 2003. Kluwer Academic Publishers.Google Scholar
  32. 32.
    Rohit Chandra, Leo Dagum, Dave Kohr, Dror Maydan, Jeff McDonald, and Ramesh Menon. Parallel Programming in OpenMP. Morgan Kaufmann, 2000.Google Scholar
  33. 33.
    Liming Chen, Nigel Shadbolt, Carole Goble, Feng Tao, Simon Cox, Colin Puleston, and Paul Smart. Towards a Knowledge-based Approach to Semantic Service Composition. In Proc. of the 2nd International Semantic Web Conference (ISWC2003), pages 319–334, Florida, USA, 2003.Google Scholar
  34. 34.
    Liming Chen, Nigel Richard Shadbolt, Feng Tao, Carole Goble, Colin Puleston, and Simon James Cox. Semantics-Assisted Problem Solving on the Semantic Grid. Computational Intelligence, 21:157–176, 2005.Google Scholar
  35. 35.
    Roberto Chinnici, Jean-Jacques Moreau, Arthur Ryman, and Sanjiva Weerawarana. Web Services Description Language (WSDL) Version 2.0. http://www.w3.org/TR/wsdl20/, 2007.
  36. 36.
    David Churches, Gabor Gombas, Andrew Harrison, Jason Maassen, Craig Robinson, Matthew Shields, Ian Taylor, and Ian Wang. Programming Scientific and Distributed Workflow with Triana Services. Concurrency and Computation: Practice & Experience, 18(10):1021–1037, 2006.Google Scholar
  37. 37.
    Condor Team. DAGMan: A Directed Acyclic Graph Manager. http://www.cs.wisc.edu/condor/dagman/, July 2005.
  38. 38.
    W. R. Cotton, R. A. Pielke, R. L. Walko, G. E. Liston, C. J. Tremback, H. Jiang, R. L. McAnelly, J. Y. Harrington, M. E. Nicholls, G. G. Carrio, and J. P. McFadden. RAMS 2001: Current status and future directions. Meteorology and Atmospheric Physics, 82:5–29, 2003.Google Scholar
  39. 39.
    Francisco Curbera, Yaron Goland, Johannes Klein, Frank Leymann, Dieter Roller, Satish Thatte, and Sanjiva Weerawarana. Business Process Execution Language for Web Services Version 1.0. http://download.boulder.ibm.com/ibmdl/pub/software/dw/specs/ws-bpel/ws-bpel1.pdf, July 2002.
  40. 40.
    John Davis II, Christopher Hylands, Bart Kienhuis, Edward A. Lee, Jie Liu, Xiaojun Liu, Lukito Muliadi, Steve Neuendorffer, Jeff Tsay, Brian Vogel, and Yuhong Xiong. Ptolemy II : Heterogeneous Concurrent Modeling and Design in Java. Technical Report UCB/ERL M01/12, EECS Department, University of California, Berkeley, 2001.Google Scholar
  41. 41.
    Ewa Deelman, Gaurang Mehta, Gurmeet Singh, Mei-Hui Su, and Karan Vahi. Workflows for e-Science – Scientific Workflows for Grids, chapter Pegasus: Mapping Large-Scale Workflows to Distributed Resources. Springer Verlag, 2007.Google Scholar
  42. 42.
    Ewa Deelman, Gurmeet Singh, Mei-Hui Su, James Blythe, Yolanda Gil, Carl Kesselman, Gaurang Mehta, Karan Vahi, G. Bruce Berriman, John Good, Anastasia Laity, Joseph C. Jacob, and Daniel S. Katz. Pegasus: a Framework for Mapping Complex Scientific Workflows onto Distributed Systems. Scientific Programming Journal, 13(2), November 2005.Google Scholar
  43. 43.
    Thierry Delaitre, Tamas Kiss, Ariel Goyeneche, Gabor Terstyanszky, Stephen Winter, and Peter Kacsuk. GEMLCA: Running Legacy Code Applications as Grid Services. Journal of Grid Computing, 3(1–2):75–90, June 2005.Google Scholar
  44. 44.
    Rubing Duan, Radu Prodan, and Thomas Fahringer. DEE: A Distributed Fault Tolerant Workflow Enactment Engine for Grid Computing. In Proceedings of the International Conference on High Performance Computing and Communications(HPCC 05), Lecture Notes in Computer Science, Sorrento, Italy, September 21–25, 2005. Springer Verlag.Google Scholar
  45. 45.
    Rubing Duan, Radu Prodan, and Thomas Fahringer. Run-time Optimization for Grid Workflow Applications. In Proceedings of 7th IEEE/ACM International Conference on Grid Computing (Grid’06), Barcelona, Spain, 2006. IEEE Computer Society Press.Google Scholar
  46. 46.
    Ziyang Duan, Arthur Bernstein, Philip Lewis, and Shiyong Lu. Semantics Based Verification and Synthesis of BPEL4WS Abstract Processes. In Proceedings of the IEEE International Conference on Web Services (ICWS ’04), page 734, Washington, DC, USA, 2004. IEEE Computer Society.Google Scholar
  47. 47.
    M. Dumas and A. H.M. ter Hofstede. UML Activity Diagrams as a Workflow Specification Language. In Proceedings of the International Conference on the Unified Modeling Language (UML’2001), volume 2185, pages 76–90, Toronto, Ontario, Canada, October 1–5, 2001. Springer-Verlag.Google Scholar
  48. 48.
    Erik Elmroth, Francisco Hernández, and Johan Tordsson. Three Fundamental Dimensions of Scientific Workflow Interoperability: Model of Computation, Language, and Execution Environment. Future Generation Computer Systems, 26(2):245–256, 2010.Google Scholar
  49. 49.
    Dietmar Erwin. UNICORE Plus Final Report - Uniform Interface to Computing Resources. http://www.unicore.eu/documentation/files/erwin-2003-UPF.pdf, 2003.
  50. 50.
    Rik Eshuis and Roel Wieringa. Comparing Petri Net and Activity Diagram Variants for Workflow Modelling - A Quest for Reactive Petri Nets. In Advances in Petri Nets: Petri Net Technology for Communication Based Systems; Lecture Notes in Computer Science (LNCS), volume 2472, pages 321–351, Heidelberg, Germany, March 9, 2003.Google Scholar
  51. 51.
    Thomas Fahringer, Radu Prodan, Rubing Duan, Jürgen Hofer, Farrukh Nadeem, Francesco Nerieri, Stefan Podlipnig, Jun Qin, Mumtaz Siddiqui, Hong-Linh Truong, Alex Villazon, and Marek Wieczorek. Workflows for eScience, Scientific Workflows for Grids, chapter ASKALON: A Development and Grid Computing Environment for Scientific Workflows. Springer Verlag, 2007.Google Scholar
  52. 52.
    Thomas Fahringer, Radu Prodan, Rubing Duan, Francesco Nerieri, Stefan Podlipnig, Jun Qin, Mumtaz Siddiqui, Hong-Linh Truong, Alex Villazon, and Marek Wieczorek. ASKALON: A Grid Application Development and Computing Environment. In Proceedings of 6th International Workshop on Grid Computing (Grid 2005), Seattle, USA, November 2005. IEEE Computer Society Press.Google Scholar
  53. 53.
    Thomas Fahringer, Jun Qin, and Stefan Hainzer. Specification of Grid Workflow Applications with AGWL: An Abstract Grid Workflow Language. In Proceedings of IEEE International Symposium on Cluster Computing and the Grid 2005 (CCGrid 2005), Cardiff, UK, May 9–12, 2005. IEEE Computer Society Press.Google Scholar
  54. 54.
    Hamid Mohammadi Fard, Radu Prodan, Thomas Fahringer, and Juan Jose Durillo Barrionuevo. A Multi-Objective Approach for Workflow Scheduling in Heterogeneous Computing Environments. In Proceeding of the 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2012), Ottawa, Canada, 2012.Google Scholar
  55. 55.
    Richard E. Fikes and Nils J. Nilsson. STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving. Artificial Intelligence, 2(3–4):189–208, 1971.Google Scholar
  56. 56.
    Ian Forster and Carl Kesselman. The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, November 1998.Google Scholar
  57. 57.
    Ian Foster. Globus Toolkit Version 4: Software for Service-Oriented Systems. In Proceedings of IFIP International Conference on Network and Parallel Computing, 2006.Google Scholar
  58. 58.
    Ian Foster and Carl Kesselman. The Globus Project: A Status Report. In Proceedings of IPPS/SPDP’98 Heterogeneous Computing Workshop, 1998.Google Scholar
  59. 59.
    Ian Foster, Hiro Kishimoto, Andreas Savva, D. Berry, A. Djaoui, A. Grimshaw, B. Horn, F. Maciel, F. Siebenlist, R. Subramaniam, J. Treadwell, and J. Von Reich. The Open Grid Services Architecture, Version 1.0. In Informational Document, Global Grid Forum (GGF), 2005.Google Scholar
  60. 60.
    Ian Foster, Jens Vöckler, Michael Wilde, and Yong Zhao. Chimera: A Virtual Data System for Representing, Querying, and Automating Data Derivation. In 14th International Conference on Scientific and Statistical Database Management (SSDBM’02), Edinburgh, Scotland, July 2002.Google Scholar
  61. 61.
    Ian Foster, Yong Zhao, Ioan Raicu, and Shiyong Lu. Cloud Computing and Grid Computing 360-Degree Compared. In Proceedings of the IEEE Grid Computing Environments (GCE08), 2008.Google Scholar
  62. 62.
    Eric Freeman, Ken Arnold, and Susanne Hupfer. JavaSpaces Principles, Patterns, and Practice. Addison-Wesley Longman Ltd., Essex, UK, UK, 1999.Google Scholar
  63. 63.
    Dennis Gannon, Randall Bramley, Geoffrey Fox, Shava Smallen, Al Rossi, Rachana Ananthakrishnan, Felipe Bertrand, Ken Chiu, Matt Farrellee, Madhu Govindaraju, Sriram Krishnan, Lavanya Ramakrishnan, Yogesh Simmhan, Alek Slominski, Yu Ma, Caroline Olariu, and Nicolas Rey-Cenvaz. Programming the Grid: Distributed Software Components, P2P and Grid Web Services for Scientific Applications. Cluster Computing, 5(3):325–336, 2002.Google Scholar
  64. 64.
    David Gelernter and Nicholas Carriero. Coordination languages and their significance. Communication of the ACM, 35(2):97–107, 1992.Google Scholar
  65. 65.
    Yolanda Gil. Workflows for e-Science – Scientific Workflows for Grids, chapter Workflow Composition: Semantic Representations for Flexible Automation. Springer Verlag, 2007.Google Scholar
  66. 66.
    Yolanda Gil, Varun Ratnakar, Ewa Deelman, Gaurang Mehta, and Jihie Kim. Wings for Pegasus: Creating Large-Scale Scientific Applications Using Semantic Representations of Computational Workflows. In Proceedings of the Nineteenth Conference on Innovative Applications of Artificial Intelligence (IAAI-07), Vancouver, British Columbia, Canada, July 2007.Google Scholar
  67. 67.
    Tristan Glatard, Gergely Sipos, Johan Montagnat, Zoltan Farkas, and Peter Kacsuk. Workflows for e-Science – Scientific Workflows for Grids, chapter Workflow Level Parametric Study Support by MOTEUR and the P-GRADE Portal, pages 279–299. Springer Verlag, Argonne National Laboratory, Argonne IL, 60430, USA, 2007.Google Scholar
  68. 68.
    gLite Team. gLite. http://glite.web.cern.ch/glite.
  69. 69.
    Globus Team. The Globus Alliance. http://www.globus.org.
  70. 70.
    Globus Team. The Globus Resource Specification Language RSL v1.0. http://www.globus.org/toolkit/docs/2.4/gram/rsl_spec1.html.
  71. 71.
    Antoon Goderis, Ulrike Sattler, and Carole Goble. Applying DLs for Workflow Reuse and Repurposing. In International Description Logics Workshop, Edinburgh, Scotland, 2005.Google Scholar
  72. 72.
    Antoon Goderis, Ulrike Sattler, Phillip Lord, and Carole Goble. Seven bottlenecks to workflow reuse and repurposing. In Fourth International Semantic Web Conference (ISWC 2005), volume 3792, pages 323–337, Galway, Ireland, 2005.Google Scholar
  73. 73.
    Li Gong. JXTA: A Network Programming Environment. IEEE Internet Computing, 5(3):88–95, 2001.Google Scholar
  74. 74.
    Madhusudhan Govindaraju, Sriram Krishnan, Kenneth Chiu, Er Slominski, Dennis Gannon, and All Bramley. XCAT 2.0: A Component-Based Programming Model for Grid Web Services. Technical Report TR562, Department of Computer Science, Indiana University, 2002.Google Scholar
  75. 75.
    Thomas R. Gruber. A Translation Approach to Portable Ontology Specifications. Knowl. Acquis., 5(2):199–220, 1993.Google Scholar
  76. 76.
    Zhijie Guan, Francisco Hernandez, Purushotham Bangalore, Jeff Gray, Anthony Skjellum, Vijay Velusamy, and Yin Liu. Grid-Flow: a Grid-Enabled Scientific Workflow System with a Petri-Net-Based Interface. Concurrency and Computation: Practice & Experience, 18(10):1115–1140, 2006.Google Scholar
  77. 77.
    Tomasz Gubała, Daniel Harezlak, Marian Bubak, and Maciej Malawski. Constructing Abstract Workflows of Applications with Workflow Composition Tool. In Proceedings of Cracow Grid Workshop (CGW’06), K-WfGrid - The Knowledge-based Workflow System for Grid Applications, 2006.Google Scholar
  78. 78.
    Tomasz Gubała, Daniel Herȩżlak, Marian Bubak, and Maciej Malawski. Semantic Composition of Scientific Workflows Based on the Petri Nets Formalism. In Proc. of the 2nd IEEE International Conference on e-Science and Grid Computing, Amsterdam, The Netherlands., December 4–6, 2006. (c) IEEE Computer Society Press.Google Scholar
  79. 79.
    Yousra BenDaly Hlaoui and Leila Jemni BenAyed. Toward an UML-Based Composition of Grid Services Workflows. In Proceedings of the 2nd international workshop on Agent-Oriented Software Engineering Challenges for Ubiquitous and Pervasive Computing (AUPC’08), pages 21–28, New York, NY, USA, 2008. ACM.Google Scholar
  80. 80.
    Jörg Hoffmann and Bernhard Nebel. The FF Planning System: Fast Plan Generation Through Heuristic Search. Journal of Artificial Intelligence Research, 14:253–302, 2001.Google Scholar
  81. 81.
    Andreas Hoheisel. User Tools and Languages for Graph-based Grid Workflows. In Grid Workflow Workshop, GGF10, Berlin, Germany, March 9, 2004.Google Scholar
  82. 82.
    Andreas Hoheisel and Martin Alt. Workflows for e-Science – Scientific Workflows for Grids, chapter Petri Nets, pages 190–207. Springer Verlag, 2007.Google Scholar
  83. 83.
    Andreas Hoheisel and Uwe Der. An XML-Based Framework for Loosely Coupled Applications on Grid Environments. Lecture Notes in Computer Science, 2657:245–254, January 2003.Google Scholar
  84. 84.
    IBM. Web Service Flow Language (WSFL 1.0). http://www-306.ibm.com/software/solutions/webservices/pdf/WSFL.pdf, May 2001.
  85. 85.
    Jena Team. Jena Semantic Web Framework API. http://jena.sourceforge.net/.
  86. 86.
    Kurt Jensen. An Introduction to the Practical Use of Coloured Petri Nets. In Lectures on Petri Nets II: Applications, Advances in Petri Nets, pages 237–292, London, UK, 1998. Springer-Verlag.Google Scholar
  87. 87.
    Alexandru Jugravu and Thomas Fahringer. JavaSymphony, a Programming Model for the Grid. In First International Workshop on Programming Paradigms for Grids and Metacomputing Systems (PPGaMS 2004), Krakow, Poland, June 2004. Springer Verlag.Google Scholar
  88. 88.
    K-Wf Grid Team. K-Wf Grid: The Knowledge-based Workflow System for Grid Applications. http://www.kwfgrid.eu.
  89. 89.
    Nicholas T. Karonis, Brian Toonen, and Ian Foster. MPICH-G2: a Grid-enabled implementation of the Message Passing Interfaces. J. Parallel Distrib. Comput., 63(5):551–563, 2003.Google Scholar
  90. 90.
  91. 91.
    Matthias Kloppmann, Dieter Koenig, Frank Leymann, Gerhard Pfau, Alan Rickayzen, Claus von Riegen, Patrick Schmidt, and Ivana Trickovic. WS-BPEL 2.0 Extensions for Sub-Processes. http://www.ibm.com/developerworks/library/specification/ws-bpelsubproc/, September 2005.
  92. 92.
    Charles H. Koelbel, David B. Loveman, and Robert S. Schreiber. The High Performance Fortran Handbook. Scientific and Engineering Computation. The MIT Press, November 1993.Google Scholar
  93. 93.
    Tevfik Kosar and Mehmet Balman. A New Paradigm: Data-aware Scheduling in Grid Computing. Future Gener. Comput. Syst., 25(4):406–413, 2009.Google Scholar
  94. 94.
    Sriram Krishnan and Dennis Gannon. XCAT3: A Framework for CCA Components as OGSA Services. In Proceedings of 9th International Workshop on High-Level Parallel Programming Models and Supportive Environments (HIPS), April 2004.Google Scholar
  95. 95.
    Sriram Krishnan, Patrick Wagstrom, and Gregor von Laszewski. GSFL: A Workflow Framework for Grid Services. Technical Report ANL/MCS-P980–0802, Argonne National Laboratory, July 2002.Google Scholar
  96. 96.
    Gregor Von Laszewski, Kaizar Amin, Mihael Hategan, Nestor J. Zaluzec, Shawn Hampton, and Albert Rossi. GridAnt: A Client-Controllable Grid Workflow System. In 37th Annual Hawaii International Conference on System Sciences (HICSS’04), Big Island, Hawaii, January 5–8, 2004. IEEE Computer Society Press.Google Scholar
  97. 97.
    Florian Lautenbacher and Bernhard Bauer. A Survey on Workflow Annotation & Composition Approaches. In Proceedings of the Workshop on Semantic Business Process and Product Lifecycle Management (SemBPM) in the context of the European Semantic Web Conference (ESWC), pages 12–23, Innsbruck, Austria, June 2007.Google Scholar
  98. 98.
    Craig Lee, Satoshi Matsuoka, Domenico Talia, Alan Sussman, M Mueller, Gabrielle Allen, and Joel Saltz. A Grid Programming Primer. Submitted to Open Grid Forum, August 2001.Google Scholar
  99. 99.
    Craig Lee and Domenico Talia. Grid Computing: Making the Global Infrastructure a Reality, chapter Grid Programming Models: Current Tools, Issues and Directions, pages 555–578. John Wiley & Sons, Ltd, 2003.Google Scholar
  100. 100.
    Edward A. Lee and Steve Neuendorffer. MoML – A Modeling Markup Language in XML – Version 0.4. Technical Memorandum UCB/ERL M00/12, University of California, Berkeley, CA 94720, March 2000.Google Scholar
  101. 101.
    Marc Lelarge, Zhen Liu, and Anton V. Riabov. Automatic Composition of Secure Workflows. Technical Report W0607–005, IBM Research Division, July 2006.Google Scholar
  102. 102.
    Melissa Lemos, Marco Antonio Casanova, Luiz Fernando Bessa Seibel, José Antonio Fernandes de Macedo, and Antonio Basílio de Miranda. Ontology-Driven Workflow Management for Biosequence Processing Systems. In Proceedings of 15th International Conference Database and Expert Systems Applications (DEXA 2004), volume 3180/2004, pages 781–790, Zaragoza, Spain, August 30-September 3, 2004. Springer.Google Scholar
  103. 103.
    Peter Li, Tom Oinn, Stian Soiland, and Douglas B. Kell. Automated Manipulation of Systems Biology Models Using libSBML within Taverna Workflows. Bioinformatics (Oxford, England), 24(2):287–289, January 2008.Google Scholar
  104. 104.
    Phillip Lord, Pinar Alper, Chris Wroe, and Carole Goble. The Semantic Web: Research and Applications, chapter Feta: A Light-Weight Architecture for User Oriented Semantic Service Discovery, pages 17–31. Springer, 2005.Google Scholar
  105. 105.
    Bertram Ludäscher, Ilkay Altintas, Chad Berkley, Dan Higgins, Efrat Jaeger, Matthew Jones, Edward A. Lee, Jing Tao, and Yang Zhao. Scientific Workflow Management and the Kepler System. Concurrency and Computation: Practice and Experience, 18(10):1039–1065, 2006.Google Scholar
  106. 106.
    Bertram Ludäscher, Ilkay Altintas, Shawn Bowers, Julian Cummings, Terence Critchlow, Ewa Deelman, David De Roure, Juliana Freire, Carole Goble, Matthew Jones, Scott Klasky, Timothy McPhillips, Norbert Podhorszki, Claudio Silva, Ian Taylor, and Mladen Vouk. Scientific Process Automation and Workflow Management. In Arie Shoshani and Doron Rotem, editors, Scientific Data Management: Challenges, Existing Technology, and Deployment, Computational Science Series, chapter 13. Chapman & Hall, 2009.Google Scholar
  107. 107.
    Akshay Luther, Rajkumar Buyya, Rajiv Ranjan, and Srikumar Venugopal. Alchemi: A.NET-Based Enterprise Grid Computing System. In ICOMP’05: Proceedings of the 6th International Conference on Internet Computing, Las Vegas, Nevada, USA, June 2005.Google Scholar
  108. 108.
    Shalil Majithia, David W.Walker, and W.A.Gray. Automated Composition of Semantic Grid Services. In S.J.Cox, editor, Proceedings of the UK e-Science All Hands Meeting 2004, Nottingham, UK, August 31 - September 3, 2004.Google Scholar
  109. 109.
    Anthony Mayer, Stephen McGough, Murtaza Gulamali, Laurie Young, Jim Stanton, Steven Newhouse, and John Darlington. Meaning and Behaviour in Grid Oriented Components. In GRID ’02: Proceedings of the Third International Workshop on Grid Computing, pages 100–111, London, UK, 2002. Springer-Verlag.Google Scholar
  110. 110.
    Anthony Mayer, Steve McGough, Nathalie Furmento, Jeremy Cohen, Murtaza Gulamali, Laurie Young, Ali Afzal, Steven Newhouse, and John Darlington. Component Models and Systems for Grid Applications, volume 1 of CoreGRID series, chapter ICENI: An Integrated Grid Middleware to Support e-Science, pages 109–124. Springer, June 2004.Google Scholar
  111. 111.
    Anthony Mayer, Steve McGough, Nathalie Furmento, William Lee, Steven Newhouse, and John Darlington. ICENI Dataflow and Workflow: Composition and Scheduling in Space and Time. In UK e-Science All Hands Meeting, pages 627–634. IOP Publishing Ltd, 2003.Google Scholar
  112. 112.
    Deborah L. McGuinness and Frank van Harmelen. OWL Web Ontology Language Overview. Technical report, The World Wide Web Consortium (W3C), 2004.Google Scholar
  113. 113.
    Timothy Mcphillips, Shawn Bowers, and Bertram Ludäscher. Collection-Oriented Scientific Workflows for Integrating and Analyzing Biological Data. In 3rd international Conference on Data Integration for the Life Sciences (DILS), Hinxton, UK, November 2006. LNCS/LNBI.Google Scholar
  114. 114.
    Timothy McPhillips, Shawn Bowers, Daniel Zinn, and Bertram Ludäscher. Scientific Workflow Design for Mere Mortals. Future Generation Computer Systems, 25(5):541–551, 2009.Google Scholar
  115. 115.
    Message Passing Interface Forum. MPI: a Message Passing Interface Standard. http://www.mpi-forum.org, June 1995.
  116. 116.
    Message Passing Interface Forum. MPI-2: Extensions to the Message Passing Interface. http://www.mpi-forum.org/, July 1997.
  117. 117.
    METEOR-S Team. METEOR-S: Semantic Web Services and Processes. http://lsdis.cs.uga.edu/projects/meteor-s/.
  118. 118.
    Harald Meyer and Mathias Weske. Automated Service Composition using Heuristic Search. In Proceedings of the Fourth International Conference on Business Process Management (BPM 2006), Vienna, Austria, 2006.Google Scholar
  119. 119.
    Microsoft. XLANG Web Services for Business Process Design. http://www.gotdotnet.com/team/xml_wsspecs/xlang-c/default.htm, 2001.
  120. 120.
    Johan Montagnat, Benjamin Isnard, Tristan Glatard, Ketan Maheshwari, and Mireille Blay Fornarino. A Data-driven Workflow Language for Grids Based on Array Programming Principles. In WORKS ’09: Proceedings of the 4th Workshop on Workflows in Support of Large-Scale Science, pages 1–10, New York, NY, USA, 2009. ACM.Google Scholar
  121. 121.
    Luc Moreau, Yong Zhao, Ian Foster, Jens Voeckler, and Michael Wilde. XDTM: The XML Data Type and Mapping for Specifying Datasets. In Lecture Notes in Computer Science: Advances in Grid Computing - EGC 2005: European Grid Conference, volume 3470, pages 495–505, Amsterdam, The Netherlands, February 14–16, 2005. Springer.Google Scholar
  122. 122.
    myExperiment Team. The myExperiment project. http://www.myexperiment.org/.
  123. 123.
    myGrid Team. The myGrid project. http://www.mygrid.org.uk/.
  124. 124.
    myGrid Team. Taverna User Manual. http://www.mygrid.org.uk/taverna2/helpset/helpset.pdf, February 2009.
  125. 125.
    Gayathri Nadarajan, Yun-Heh Chen-Burger, and James Malone. Semantic-Based Workflow Composition for Video Processing in the Grid. In Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence, Hong Kong, China, December 12–18, 2006.Google Scholar
  126. 126.
    Farrukh Nadeem and Thomas Fahringer. Predicting the Execution Time of Grid Workflow Applications through Local Learning. In Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis (SC09), Portland, Oregon, US, 2009.Google Scholar
  127. 127.
    Farrukh Nadeem, Radu Prodan, and Thomas Fahringer. Characterizing, Modeling and Predicting Dynamic Resource Availability in a Large Scale Multi-Purpose Grid. In Proc. of the Eighth IEEE International Symposium on Cluster Computing and the Grid (CCGrid 2008), Lyon, France, May 19–22, 2008. IEEE Computer Society.Google Scholar
  128. 128.
    Francesco Nerieri, Radu Prodan, Thomas Fahringer, and Hong-Linh Truong. Overhead Analysis of Grid Workflow Applications. In Proceedings of the IEEE/ACM International Workshop on Grid Computing (Grid2006), volume 0, pages 17–24, Los Alamitos, CA, USA, 2006. IEEE Computer Society.Google Scholar
  129. 129.
    OASIS Web Services Business Process Execution Language (WSBPEL) TC. Web Services Business Process Execution Language Version 2.0 – OASIS Standard. http://docs.oasis-open.org/wsbpel/2.0/wsbpel-v2.0.html, April 2007.
  130. 130.
    Object Management Group. Business Process Modeling Notation (BPMN). http://www.bpmn.org/.
  131. 131.
    OGF Community. Open Grid Forum. http://www.ogf.org.
  132. 132.
    OGF JSDL Workgroup. Job Submission Description Language (JSDL) Specification, Version 1.0. http://www.gridforum.org/documents/GFD.56.pdf.
  133. 133.
    Tom Oinn, Matthew Addis, Justin Ferris, Darren Marvin, Martin Senger, Mark Greenwood, Tim Carver, Kevin Glover, Matthew R. Pocock, Anil Wipat, and Peter Li. Taverna: a Tool for the Composition and Enactment of Bioinformatics Workflows. Bioinformatics Journal, 20(17):3045–3054, June 2004.Google Scholar
  134. 134.
    Organization for the Advancement of Structured Information Standards (OASIS). http://www.oasis-open.org/.
  135. 135.
    Chun Ouyang. Data Manipulation in YAWL. http://sky.fit.qut.edu.au/~terhofst/YAWLdocs/YAWLDataManual-beta7.pdf, November 2005.
  136. 136.
    P-GRADE Team. P-GRADE: Parallel Grid Run-time and Application Development Environment. http://www.p-grade.hu/.
  137. 137.
    Bijan Parsia and Peter F. Patel-Schneider. OWL 2 Web Ontology Language: Primer. Technical report, The World Wide Web Consortium (W3C), 2008.Google Scholar
  138. 138.
    Cesare Pautasso and Gustavo Alonso. Parallel Computing Patterns for Grid Workflows. In Proceedings of the Workshop on Workflows in Support of Large-Scale Science, Paris, France, June 19–23, 2006.Google Scholar
  139. 139.
    Pegasus-WMS Team. Workflow Management System (Pegasus-WMS). http://pegasus.isi.edu/wms/.
  140. 140.
    James Lyle Peterson. Petri Net Theory and the Modeling of Systems. Prentice Hall PTR, Upper Saddle River, NJ, USA, 1981.Google Scholar
  141. 141.
    Kassian Plankensteiner, Johan Montagnat, and Radu Prodan. IWIR: A Language Enabling Portability Across Grid Workflow Systems. In WORKS’11: Proceedings of the 6th Workshop on Workflows in Support of Large-Scale Science, Seattle, USA, November 12–18, 2011.Google Scholar
  142. 142.
    Kassian Plankensteiner, Radu Prodan, Thomas Fahringer, Johan Montagnat, Andrew Harrison, Tristan Glatard, Gabor Hermann, and Miklos Kozlovsky. IWIR Specification v1.1. http://www.shiwa-workflow.eu/documents/10753/55350/IWIR+v1.1+Specification, March 2011.
  143. 143.
    S. Pllana, T. Fahringer, J. Testori, S. Benkner, and I. Brandic. Towards an UML Based Graphical Representation of Grid Workflow Applications. In 2nd European Across Grids Conference, Nicosia, Cyprus, January 2004. Springer-Verlag, 2004.Google Scholar
  144. 144.
    Radu Prodan and Thomas Fahringer. ZEN: A Directive-based Experiment Specification Language for Performance and Parameter Studies of Parallel and Distributed Scientific Applications. International Journal of High Performance Computing and Networking, 2003.Google Scholar
  145. 145.
    Radu Prodan and Thomas Fahringer. Overhead Analysis of Scientific Workflows in Grid Environments. IEEE Trans. Parallel Distrib. Syst., 19(3):378–393, 2008.Google Scholar
  146. 146.
  147. 147.
    Jun Qin and Thomas Fahringer. Advanced Data Flow Support for Scientific Grid Workflow Applications. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC07), Reno, NV, USA, November 10–16, 2007. IEEE Computer Society Press.Google Scholar
  148. 148.
    Jun Qin and Thomas Fahringer. A Novel Domain Oriented Approach for Scientific Grid Workflow Composition. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC08), Austin, Texas, USA, November 15–21, 2008. IEEE Computer Society Press.Google Scholar
  149. 149.
    Jun Qin, Thomas Fahringer, and Maximilian Berger. Towards Workflow Sharing and Reuse in the ASKALON Grid Environment. In Proceedings of Cracow Grid Workshop (CGW’08), Cracow, Poland, October 2008.Google Scholar
  150. 150.
    Jun Qin, Thomas Fahringer, and Sabri Pllana. UML Based Grid Workflow Modeling under ASKALON. In Proceedings of 6th Austrian-Hungarian Workshop on Distributed and Parallel Systems, Innsbruck, Austria, September 21–23, 2006. Springer-Verlag.Google Scholar
  151. 151.
    Jun Qin, Thomas Fahringer, and Radu Prodan. A Novel Graph Based Approach for Automatic Composition of High Quality Grid Workflows. In Proceedings of the 18th International Symposium on High Performance Distributed Computing (HPDC 2009), Garching, Germany, June 11–13, 2009. ACM Press.Google Scholar
  152. 152.
    David De Roure, Mark A. Baker, and Nicholas R. Jennings. Grid Computing: Making the Global Infrastructure a Reality, chapter The Evolution of the Grid, pages 65–100. John Wiley & Sons, 2003.Google Scholar
  153. 153.
    David De Roure, Carole Goble, and Robert Stevens. Designing the myExperiment Virtual Research Environment for the Social Sharing of Workflows. In E-SCIENCE ’07: Proceedings of the Third IEEE International Conference on e-Science and Grid Computing, pages 603–610, Washington, DC, USA, 2007. IEEE Computer Society.Google Scholar
  154. 154.
    Nick Russell, Arthur H.M. ter Hofstede, David Edmond, and Wil M.P. van der Aalst. Workflow Data Patterns (Revised Version). Technical Report FIT-TR-2004–01, Queensland University of Technology, Brisbane, Australia, 2004.Google Scholar
  155. 155.
    Leonardo Salayandía, Paulo Pinheiro da Silva, Ann Q. Gates, and Alvaro Rebellon. A Model-Based Workflow Approach for Scientific Applications. In Proceedings of the 6th OOPSLA Workshop on Domain-Specific Modeling, 2006.Google Scholar
  156. 156.
    Leonardo Salayandía, Paulo Pinheiro da Silva, Ann Q. Gates, and Flor Salcedo. Workflow-Driven Ontologies: An Earth Sciences Case Study. In Proceedings of Second IEEE International Conference on e-Science and Grid Computing (e-Science’06), volume 0, page 17, Los Alamitos, CA, USA, 2006. IEEE Computer Society.Google Scholar
  157. 157.
    Mitsuhisa Sato, Taisuke Boku, and Daisuke Takahashi. OmniRPC: a Grid RPC system for Parallel Programming in Cluster and Grid Environment. In CCGRID ’03: Proceedings of the 3st International Symposium on Cluster Computing and the Grid, page 206, Washington, DC, USA, 2003. IEEE Computer Society.Google Scholar
  158. 158.
    S. Schindler, W. Kapferer, W. Domainko, M. Mair, E. van Kampen, T. Kronberger, S. Kimeswenger, M. Ruffert, O. Mangete, and D. Breitschwerdt. Metal Enrichment Processes in the Intra-Cluster Medium. Astronomy and Astrophysics, 435:L25–L28, May 2005.Google Scholar
  159. 159.
    Felix Schüller, Jun Qin, Farrukh Nadeem, Radu Prodan, Thomas Fahringer, and Georg Mayr. Performance, Scalability and Quality of the Meteorological Grid Workflow MeteoAG. In Proceedings of 2nd Austrian Grid Symposium, Innsbruck, Austria, September 21–23, 2006. OCG Verlag.Google Scholar
  160. 160.
  161. 161.
    Semantic Grid Community. Semantic Grid. http://www.semanticgrid.org.
  162. 162.
    Keith Seymour, Hidemoto Nakada, Satoshi Matsuoka, Jack Dongarra, Craig Lee, and Henri Casanova. Overview of GridRPC: A Remote Procedure Call API for Grid Computing. In GRID ’02: Proceedings of the Third International Workshop on Grid Computing, pages 274–278, London, UK, 2002. Springer-Verlag.Google Scholar
  163. 163.
    SHIWA Team. SHIWA: SHaring Interoperable Workflows for Large-Scale Scientific Simulation on Available DCIs. http://www.shiwa-workflow.eu/, 2011.
  164. 164.
    Mumtaz Siddiqui, Alex Villazón, and Thomas Fahringer. Grid capacity planning with negotiation-based advance reservation for optimized QoS. In SC’06: Proceedings of the 2006 ACM/IEEE conference on Supercomputing, page 103, New York, NY, USA, 2006. ACM.Google Scholar
  165. 165.
    Mumtaz Siddiqui, Alex Villazon, Jurgen Hofer, and Thomas Fahringer. GLARE: A Grid Activity Registration, Deployment and Provisioning Framework. In SC’05: Proceedings of the 2005 ACM/IEEE conference on Supercomputing, Seattle, WA, USA, 2005. IEEE Computer Society.Google Scholar
  166. 166.
    Laura Silva, Gian Luigi Granato, Alessandro Bressan, Cedric Lacey, Carlton M. Baugh, Shaun Cole, and Carlos S. Frenk. Modelling Dust in Galactic SEDs: Application to Semi-Analytical Galaxy Formation Models. Astrophysics and Space Science, 276(2–4):1073–1078, 2001.Google Scholar
  167. 167.
    Harold Soh, Shazia Haque, Weili Liao, and Rajkumar Buyya. Advanced Parallel and Distributed Computing, chapter Grid Programming Models and Environments, pages 141–173. Nova Science Publishers, Inc., 2006.Google Scholar
  168. 168.
    Harold Soh, Shazia Haque, Weili Liao, Krishna Nadiminti, and Rajkumar Buyya. GTPE: A Thread Programming Environment for the Grid. In Proceedings of the 13th International Conference on Advanced Computing and Communications, Coimbatore, Tamil Nadu, India, December 2005.Google Scholar
  169. 169.
    Clemens Szyperski. Component Software: Beyond Object-Oriented Programming. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 2002.Google Scholar
  170. 170.
    Wei Tan, Paolo Missier, Ravi Madduri, and Ian Foster. Building Scientific Workflow with Taverna and BPEL: A Comparative Study in caGrid. pages 118–129, 2009.Google Scholar
  171. 171.
    Ian Taylor, Matthew Shields, Ian Wang, and Andrew Harrison. Visual Grid Workflow in Triana. Journal of Grid Computing, 3(3–4):153–169, September 2005.Google Scholar
  172. 172.
    Ian Taylor, Matthew Shields, Ian Wang, and Andrew Harrison. Workflows for e-Science – Scientific Workflows for Grids, chapter The Triana Workflow Environment: Architecture and Applications. Springer Verlag, 2007.Google Scholar
  173. 173.
    Ian Taylor, Matthew Shields, Ian Wang, and Omer Rana. Triana Applications within Grid Computing and Peer to Peer Environments. Journal of Grid Computing, 1(2):199–217, 2003.Google Scholar
  174. 174.
    Ian Taylor, Ian Wang, Matthew Shields, and Shalil Majithia. Distributed computing with Triana on the Grid. Concurrency and Computation: Practice and Experience, 2005.Google Scholar
  175. 175.
    Arthur Ter Hofstede and Wil van der Aalst. Workflow Patterns: On the Expressive Power of (Petri-net-based) Workflow Languages. In Proceeding of Fourth Workshop and Tutorial on Practical Use of Coloured Petri Nets and the CPN Tools, August 2002.Google Scholar
  176. 176.
    The Object Management Group (OMG). UML Activity Diagram. http://www.omg.org/spec/UML/2.2/.
  177. 177.
    The Object Management Group (OMG). Unified Modeling Language (UML). http://www.omg.org/spec/UML/2.2/.
  178. 178.
    The Workflow Management Coalition (WfMC). http://www.wfmc.org.
  179. 179.
    The Workflow Management Coalition (WfMC). Process Definition Interface – XML Process Definition Language (XPDL) Version 2.0. http://www.wfmc.org/xpdl.htm, October 2005.
  180. 180.
    The Workflow Management Coalition (WfMC). Process Definition Interface – XML Process Definition Language (XPDL) Version 2.1. http://www.wfmc.org/xpdl.html, March 2008.
  181. 181.
    The World Wide Web Consortium. XML Schema Datatypes. http://www.w3.org/TR/xmlschema-2/.
  182. 182.
    The World Wide Web Consortium. RDF Vocabulary Description Language 1.0: RDF Schema. http://www.w3.org/TR/rdf-schema/, 2004.
  183. 183.
    The World Wide Web Consortium. Resource Description Framework (RDF). http://www.w3.org/TR/REC-rdf-syntax/, 2004.
  184. 184.
    The World Wide Web Consortium (W3C). OWL-S: Semantic Markup for Web Services. http://www.w3.org/Submission/OWL-S/.
  185. 185.
    The World Wide Web Consortium (W3C). Simple Object Access Protocol (SOAP) Version 1.2. http://www.w3.org/TR/2007/REC-soap12-part0-20070427/.
  186. 186.
    The World Wide Web Consortium (W3C). Web Service Semantics - WSDL-S. http://www.w3.org/Submission/WSDL-S/.
  187. 187.
    The World Wide Web Consortium (W3C). XPATH. http://www.w3.org/TR/xpath.html.
  188. 188.
    The World Wide Web Consortium (W3C). XQuery. http://www.w3.org/TR/xquery/.
  189. 189.
    The World Wide Web Consortium (W3C). Web Services Description Language (WSDL) Version 2.0. http://www.w3.org/TR/wsdl20/, 2007.
  190. 190.
  191. 191.
    Daniele Turi, Paolo Missier, Carole Goble, David D. Roure, and Tom Oinn. Taverna Workflows: Syntax and Semantics. In Proceedings of the IEEE International Conference on e-Science and Grid Computing, pages 441–448, Bangalore, India, December 2007.Google Scholar
  192. 192.
    UNICORE Team. Uniform Interface to Computing Resources (UNICORE). http://www.unicore.eu.
  193. 193.
    Wil M.P. van der Aalst and Arthur H.M. ter Hofstede. YAWL: Yet Another Workflow Language. Information Systems, 30(4):245–275, June 2005.Google Scholar
  194. 194.
    Snigdha Verma, Jarek Gawor, Gregor Von Laszewski, and Manish Parashar. A CORBA Commodity Grid Kit. Concurrency and Computation: Practice and Experience, 13:8–9, 2001.Google Scholar
  195. 195.
    Gregor von Laszewski, Mihael Hategan, and Deepti Kodeboyina. Workflows for e-Science – Scientific Workflows for Grids, chapter Java CoG Kit Workflow, pages 340–356. Springer Verlag, Argonne National Laboratory, Argonne IL, 60430, USA, 2007.Google Scholar
  196. 196.
    Gregor von Laszewski and Mike Hategan. Java CoG Kit Workflow Guide. http://wiki.cogkit.org/wiki/Java_CoG_Kit_Workflow_Guide, 2006.
  197. 197.
    Gregor von Laszewski and Deepti Kodeboyina. A Repository Service for Grid Workflow Components. In International Conference on Autonomic and Autonomous Systems International Conference on Networking and Services, Papeete, Tahiti, French Polynesia, October 23–28, 2005. IEEE.Google Scholar
  198. 198.
    Ingo Wassink, Paul E. van der Vet, Katy Wolstencroft, Pieter B.T. Neerincx, Marco Roos, Han Rauwerda, and Timo M. Breit. Analysing Scientific Workflows: Why Workflows Not Only Connect Web Services. IEEE Congress on Services, 0:314–321, 2009.Google Scholar
  199. 199.
    Wave-Front BV. FLOWer 3 Designers Guide. http://www.pallas-athena.com/, 2004.
  200. 200.
    Marek Wieczorek, Stefan Podlipnig, Radu Prodan, and Thomas Fahringer. Bi-criteria Scheduling of Scientific Workflows for the Grid. In Proc. of the Eighth IEEE International Symposium on Cluster Computing and the Grid (CCGrid 2008), Lyon, France, May 2008. IEEE Computer Society.Google Scholar
  201. 201.
    Marek Wieczorek, Radu Prodan, and Thomas Fahringer. Scheduling of Scientific Workflows in the ASKALON Grid Environment. ACM SIGMOD Record, 35(3), 2005.Google Scholar
  202. 202.
    Zixin Wu, Ajith Ranabahu, Karthik Gomadam, Amit P. Sheth, and John A. Miller. Automatic Composition of Semantic Web Services using Process and Data Mediation. Technical report, LSDIS lab, University of Georgia, February 2007.Google Scholar
  203. 203.
    Jia Yu and Rajkumar Buyya. A Novel Architecture for Realizing Grid Workflow using Tuple Spaces. In Proceedings of Fifth IEEE/ACM International Workshop on Grid Computing, Pittsburgh, PA, November 2004.Google Scholar
  204. 204.
    Jia Yu and Rajkumar Buyya. A Taxonomy of Workflow Management Systems for Grid Computing. Technical Report GRIDS-TR-2005-1, Grid Computing and Distributed Systems Laboratory, University of Melbourne, Australia, March 10, 2005.Google Scholar
  205. 205.
    Jianting Zhang. Ontology-Driven Composition and Validation of Scientific Grid Workflows in Kepler: a Case Study of Hyperspectral Image Processing. In Proceedings of 5th International Conference on Grid and Cooperative Computing Workshops, 2006.Google Scholar
  206. 206.
    Yong Zhao, Jed Dobson, Ian Foster, Luc Moreau, and Michael Wilde. A Notation and System for Expressing and Executing Cleanly Typed Workflows on Messy Scientific Data. Sigmod Record, 34(3), September 2005.Google Scholar
  207. 207.
    Yong Zhao, Michael Wilde, and Ian Foster. Workflows for eScience, Scientific Workflows for Grids, chapter Virtual Data Language: A Typed Workflow Notation for Diversely Structured Scientific Data. Springer Verlag, 2007.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jun Qin
    • 1
  • Thomas Fahringer
    • 2
  1. 1.Amadeus Data Processing GmbHErdingGermany
  2. 2.Universität InnsbruckInnsbruckAustria

Personalised recommendations