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CCGRID
2008
IEEE
14 years 4 months ago
Data Management Challenges of Data-Intensive Scientific Workflows
Scientific workflows play an important role in today’s science. Many disciplines rely on workflow technologies to orchestrate the execution of thousands of computational tasks. ...
Ewa Deelman, Ann L. Chervenak
GRID
2004
Springer
14 years 3 months ago
Phoenix: Making Data-Intensive Grid Applications Fault-Tolerant
A major hurdle facing data intensive grid applications is the appropriate handling of failures that occur in the grid-environment. Implementing the fault-tolerance transparently a...
George Kola, Tevfik Kosar, Miron Livny
HCW
2000
IEEE
14 years 2 months ago
Design of a Framework for Data-Intensive Wide-Area Applications
Applications that use collections of very large, distributed datasets have become an increasingly important part of science and engineering. With high performance wide-area networ...
Michael D. Beynon, Tahsin M. Kurç, Alan Sus...
CLOUD
2010
ACM
14 years 2 months ago
Comet: batched stream processing for data intensive distributed computing
Batched stream processing is a new distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired...
Bingsheng He, Mao Yang, Zhenyu Guo, Rishan Chen, B...
CLUSTER
2011
IEEE
12 years 9 months ago
A Framework for Data-Intensive Computing with Cloud Bursting
—For many organizations, one attractive use of cloud resources can be through what is referred to as cloud bursting or the hybrid cloud. These refer to scenarios where an organiz...
Tekin Bicer, David Chiu, Gagan Agrawal