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CCGRID
2005
IEEE
14 years 4 months ago
Task scheduling strategies for workflow-based applications in grids
Grid applications require allocating a large number of heterogeneous tasks to distributed resources. A good allocation is critical for efficient execution. However, many existing ...
James Blythe, S. Jain, Ewa Deelman, Yolanda Gil, K...
ICDE
2011
IEEE
258views Database» more  ICDE 2011»
13 years 2 months ago
SystemML: Declarative machine learning on MapReduce
Abstract—MapReduce is emerging as a generic parallel programming paradigm for large clusters of machines. This trend combined with the growing need to run machine learning (ML) a...
Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D....
ICDCS
2007
IEEE
14 years 5 months ago
Streaming Algorithms for Robust, Real-Time Detection of DDoS Attacks
Effective mechanisms for detecting and thwarting Distributed Denial-of-Service (DDoS) attacks are becoming increasingly important to the success of today’s Internet as a viable ...
Sumit Ganguly, Minos N. Garofalakis, Rajeev Rastog...
EDBT
2010
ACM
155views Database» more  EDBT 2010»
14 years 5 months ago
Reducing metadata complexity for faster table summarization
Since the visualization real estate puts stringent constraints on how much data can be presented to the users at once, table summarization is an essential tool in helping users qu...
K. Selçuk Candan, Mario Cataldi, Maria Luis...
PVLDB
2010
178views more  PVLDB 2010»
13 years 9 months ago
Hadoop++: Making a Yellow Elephant Run Like a Cheetah (Without It Even Noticing)
MapReduce is a computing paradigm that has gained a lot of attention in recent years from industry and research. Unlike parallel DBMSs, MapReduce allows non-expert users to run co...
Jens Dittrich, Jorge-Arnulfo Quiané-Ruiz, A...