We present STAR, a self-tuning algorithm that adaptively sets numeric precision constraints to accurately and efficiently answer continuous aggregate queries over distributed data...
Navendu Jain, Michael Dahlin, Yin Zhang, Dmitry Ki...
Data streaming systems are becoming essential for monitoring applications such as financial analysis and network intrusion detection. These systems often have to process many simi...
Sailesh Krishnamurthy, Chung Wu, Michael J. Frankl...
Supervised learning is a classic data mining problem where one wishes to be be able to predict an output value associated with a particular input vector. We present a new twist on...
David R. Musicant, Janara M. Christensen, Jamie F....
In this paper we propose a new query processing method for the OLAP Enabled Grid, which blends sophisticated cache extraction techniques and data grid scheduling to efficiently s...
Michael Lawrence, Frank K. H. A. Dehne, Andrew Rau...
1 Scalable resource monitoring and discovery are essential to the planet-scale infrastructures such as Grids and PlanetLab. This paper proposes a scalable Grid monitoring architect...