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2Karma2: Provenance Management for Data-Driven Workflows
Y. Simmhan, B. Plale, and D. Gannon. International Journal of Web Services Research (IJWSR), 5 (2): 1--22 (2008)IF 0.371, CORE C.
10 years ago by @simmhan
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escience,
karma,
msr,
peer
provenance,
reviewed
workflow,
escience,karma,msr,peerprovenance,reviewedworkflow,
(0)
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2Provenance for Scientific Workflows: Towards Reproducible Research
R. Barga, Y. Simmhan, E. Withana, S. Sahoo, J. Jackson, and N. Araujo. Data Engineering Bulletin (DEB), 33 (3): 50--59 (September 2010)
10 years ago by @simmhan
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msr,
peer
provenance,
reviewed
trident,
workflow,
msr,peerprovenance,reviewedtrident,workflow,
(0)
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2Analysis of approaches for supporting the Open Provenance Model: A case study of the Trident workflow workbench
Y. Simmhan, and R. Barga. Future Generation Computer Systems (FGCS), 27 (6): 790--796 (2011)IF 1.978, CORE A.
10 years ago by @simmhan
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challenge,
inter-operability,
msr,
opm,
peer
provenance
provenance,
reviewed
trident,
workflow,
challenge,inter-operability,msr,opm,peerprovenanceprovenance,reviewedtrident,workflow,
(0)
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3Realization of Dynamically Adaptive Weather Analysis and Forecasting in LEAD: Four Years Down the Road
L. Ramakrishnan, Y. Simmhan, and B. Plale. International Conference on Computational Science (ICCS), volume 4487 of Lecture Notes in Computer Science (LNCS), page 1122-1129. Springer Berlin / Heidelberg, (2007)CORE A.
10 years ago by @simmhan
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LEAD,
escience,
iu,
peer
reviewed
workflow,
LEAD,escience,iu,peerreviewedworkflow,
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3Efficient scheduling of scientific workflows in a high performance computing cluster
R. Barga, D. Fay, D. Guo, S. Newhouse, Y. Simmhan, and A. Szalay. International Workshop on Challenges of Large Applications in Distributed Environments (CLADE), page 63-68. ACM, (2008)CORE C.
10 years ago by @simmhan
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data
eScience,
hpc,
intensive,
msr,
peer
reviewed
scheduling,
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dataeScience,hpc,intensive,msr,peerreviewedscheduling,workflow,
(0)
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4Provenance Information Model of Karma Version 3
B. Cao, B. Plale, G. Subramanian, E. Robertson, and Y. Simmhan. International Workshop on Scientific Workflows (SWF), page 348-351. IEEE, (July 2009)
10 years ago by @simmhan
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karma,
msr,
peer
provenance,
reviewed
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karma,msr,peerprovenance,reviewedworkflow,
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2Streaming satellite data to cloud workflows for on-demand computing of environmental data products
D. Zinn, Q. Hart, B. Ludascher, and Y. Simmhan. Workshop on Workflows in Support of Large-Scale Science (WORKS), page 1-8. IEEE, (November 2010)
10 years ago by @simmhan
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cloud,
escience,
peer
reviewed
streaming,
usc,
workflow,
cloud,escience,peerreviewedstreaming,usc,workflow,
(0)
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2BReW: Blackbox resource selection for e-Science workflows
Y. Simmhan, E. Soroush, C. van Ingen, D. Agarwal, and L. Ramakrishnan. Workshop on Workflows in Support of Large-Scale Science (WORKS), page 1-10. IEEE, (November 2010)
10 years ago by @simmhan
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cloud,
escience,
msr,
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reviewed
scheduling,
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cloud,escience,msr,peerreviewedscheduling,workflow,
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3Bridging the Gap between Desktop and the Cloud for eScience Applications
Y. Simmhan, C. van Ingen, G. Subramanian, and J. Li. International Cloud Computing Conference (CLOUD), page 474-481. IEEE, (July 2010)CORE B.
10 years ago by @simmhan
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cloud,
escience,
generic
genomics,
msr,
peer
reviewed
worker,
workflow,
cloud,escience,genericgenomics,msr,peerreviewedworker,workflow,
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2Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids
Y. Simmhan, V. Agarwal, S. Aman, A. Kumbhare, S. Natarajan, N. Rajguru, I. Robinson, S. Stevens, W. Yin, Q. Zhou and 1 other author(s). IEEE International Scalable Computing Challenge (SCALE), page 1--4. (2012)First Prize.
10 years ago by @simmhan
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USC,
floe,
grid,
hadoop,
information
integration,
openplanet,
peer
reviewed,
short
smart
workflow,
USC,floe,grid,hadoop,informationintegration,openplanet,peerreviewed,shortsmartworkflow,
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3Continuous Dataflow Update Strategies for Mission-Critical Applications
C. Wickramaarachchi, and Y. Simmhan. IEEE Internatrional Conference on eScience (eScience) CORE-A, (2013)
10 years ago by @simmhan
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cloud,
continuous
dataflow,
peer
reviewed
usc,
workflow,
cloud,continuousdataflow,peerreviewedusc,workflow,
(0)
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1Exploiting Cloud Elasticity to Enhance the Value of Dynamic, Continuous Dataflows
A. Kumbhare, Y. Simmhan, and V. Prasanna. IEEE/ACM International Conference for High Performance Computing Networking, Storage, and Analysis (SC) CORE A, (2013)To Appear.
10 years ago by @simmhan
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cloud,
continuous
dataflow,
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reviewed
usc,
workflow,
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(0)
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4PLAStiCC: Predictive Look-Ahead Scheduling for Continuous dataflows on Clouds
A. Kumbhare, Y. Simmhan, and V. Prasanna. (2014)Under review.
10 years ago by @simmhan
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cloud,
continuous
dataflow,
floe,
iisc,
peer
reviewed
usc,
workflow,
cloud,continuousdataflow,floe,iisc,peerreviewedusc,workflow,
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1Pan-STARRS: Learning to Ride the Data Tsunami
M. Nieto-Santisteban, Y. Simmhan, R. Barga, L. Dobos, J. Heasley, C. Holmberg, N. Li, M. Shipway, A. Szalay, C. van Ingen and 1 other author(s). Microsoft Research eScience Workshop, Microsoft, (December 2008)Talk.
10 years ago by @simmhan
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data
escience,
hpc,
management,
msr,
panstarrs,
talk
trident,
workflow,
dataescience,hpc,management,msr,panstarrs,talktrident,workflow,
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1GrayWulf: Conquering Astronomical Databases
M. Nieto-Santisteban, T. Budavari, L. Dobos, N. Li, M. Shipway, A. Szalay, A. Thakar, S. Werner, R. Wilton, Y. Simmhan and 3 other author(s). Astronomical Data Analysis Software and Systems (ADASS), Astronomical Society of the Pacific, (November 2008)Talk.
10 years ago by @simmhan
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data
escience,
management,
msr,
panstarrs,
talk
workflow,
dataescience,management,msr,panstarrs,talkworkflow,
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1Bridging the Gap between the Cloud and an eScience Application Platform
Y. Simmhan, C. van Ingen, G. Subramanian, and J. Li. MSR-TR-2009-2021. Microsoft Research, (November 2009)
10 years ago by @simmhan
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cloud,
escience,
generic
genomics
msr,
worker,
workflow,
cloud,escience,genericgenomicsmsr,worker,workflow,
(0)
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1Towards Reliable, Performant Workflows for Streaming-Applications on Cloud Platforms
D. Zinn, Q. Hart, T. McPhillips, B. Ludascher, Y. Simmhan, M. Giakkoupis, and and Viktor K. Prasanna. CSE-2010-23. Computer Science Department, UC Davis, (December 2010)
10 years ago by @simmhan
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cloud,
escience
streaming,
usc,
workflow,
cloud,esciencestreaming,usc,workflow,
(0)
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1Special Section: The third provenance challenge on using the open provenance model for interoperability
Y. Simmhan, P. Groth, and L. Moreau. Future Generation Computer Systems (FGCS), 27 (6): 737-742 (2011)CORE A.
10 years ago by @simmhan
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challenge,
editorial
inter-operability,
msr,
opm,
provenance
provenance,
trident,
workflow,
challenge,editorialinter-operability,msr,opm,provenanceprovenance,trident,workflow,
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1Floe: A Continuous Dataflow Framework for Dynamic Cloud Applications
Y. Simmhan, and A. Kumbhare. University of Southern California, (2013)
10 years ago by @simmhan
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cloud,
continuous
dataflow
usc,
workflow,
cloud,continuousdataflowusc,workflow,
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publications (hide)19
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2Karma2: Provenance Management for Data-Driven Workflows

2Provenance for Scientific Workflows: Towards Reproducible Research

2Analysis of approaches for supporting the Open Provenance Model: A case study of the Trident workflow workbench

3Realization of Dynamically Adaptive Weather Analysis and Forecasting in LEAD: Four Years Down the Road

3Efficient scheduling of scientific workflows in a high performance computing cluster

4Provenance Information Model of Karma Version 3

2Streaming satellite data to cloud workflows for on-demand computing of environmental data products

2BReW: Blackbox resource selection for e-Science workflows

3Bridging the Gap between Desktop and the Cloud for eScience Applications

2Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids

3Continuous Dataflow Update Strategies for Mission-Critical Applications

1Exploiting Cloud Elasticity to Enhance the Value of Dynamic, Continuous Dataflows

4PLAStiCC: Predictive Look-Ahead Scheduling for Continuous dataflows on Clouds

1Pan-STARRS: Learning to Ride the Data Tsunami

1GrayWulf: Conquering Astronomical Databases

1Bridging the Gap between the Cloud and an eScience Application Platform

1Towards Reliable, Performant Workflows for Streaming-Applications on Cloud Platforms

1Special Section: The third provenance challenge on using the open provenance model for interoperability

1Floe: A Continuous Dataflow Framework for Dynamic Cloud Applications

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