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GRID
2004
Springer
14 years 1 months ago
High Performance Threaded Data Streaming for Large Scale Simulations
We have developed a threaded parallel data streaming approach using Logistical Networking (LN) to transfer multi-terabyte simulation data from computers at NERSC to our local anal...
Viraj Bhat, Scott Klasky, Scott Atchley, Micah Bec...
IPPS
2009
IEEE
14 years 2 months ago
On the tradeoff between playback delay and buffer space in streaming
We consider the following basic question: a source node wishes to stream an ordered sequence of packets to a collection of receivers, which are distributed among a number of clust...
Alix L. H. Chow, Leana Golubchik, Samir Khuller, Y...
CN
2006
163views more  CN 2006»
13 years 7 months ago
A framework for mining evolving trends in Web data streams using dynamic learning and retrospective validation
The expanding and dynamic nature of the Web poses enormous challenges to most data mining techniques that try to extract patterns from Web data, such as Web usage and Web content....
Olfa Nasraoui, Carlos Rojas, Cesar Cardona
CLOUD
2010
ACM
14 years 23 days 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...
COMAD
2009
13 years 8 months ago
Categorizing Concepts for Detecting Drifts in Stream
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
Sharanjit Kaur, Vasudha Bhatnagar, Sameep Mehta, S...