Elasticity in the cloud
By David Chiu, March 2010
By David Chiu, March 2010
By Ryan K. L. Ko, March 2010
Computers continue to get faster exponentially, but the computational demands of science are growing even faster. Extreme requirements arise in at least three areas.
By David P. Anderson, March 2010
Despite its promise, most cloud computing innovations have been almost exclusively driven by a few industry leaders, such as Google, Amazon, Yahoo!, Microsoft, and IBM. The involvement of a wider research community, both in academia and industrial labs, has so far been patchy without a clear agenda. In our opinion, the limited participation stems from the prevalent view that clouds are mostly an engineering and business-oriented phenomenon based on stitching together existing technologies and tools.
By Ymir Vigfusson, Gregory Chockler, March 2010
In recent years, empirical science has been evolving from physical experimentation to computation-based research. In astronomy, researchers seldom spend time at a telescope, but instead access the large number of image databases that are created and curated by the community [42]. In bioinformatics, data repositories hosted by entities such as the National Institutes of Health [29] provide the data gathered by Genome-Wide Association Studies and enable researchers to link particular genotypes to a variety of diseases.
By Gideon Juve, Ewa Deelman, March 2010
By Sumit Narayan, Chris Heiden, March 2010
Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. With this pay-as-you-go model of computing, cloud solutions are seen as having the potential to both dramatically reduce costs and increase the rapidity of development of applications.
By Ramaswamy Chandramouli, Peter Mell, March 2010
At the turn of the 20th century, companies stopped generating their own power and plugged into the electricity grid. In his now famous book The Big Switch, Nick Carr analogizes those events of a hundred years ago to the tectonic shift taking place in the technology industry today.
By Guy Rosen, March 2010
This article describes a technique to visualize query results, representing purchase orders placed on Amazon.com, along a traditional 2-D scatter plot and a space-filling spiral. We integrate 3-D objects that vary their spatial placement, color, and texture properties into a visualization algorithm. This algorithm represents important aspects of a purchase order based on experimental results from human vision, computer graphics, and psychology. The resulting visual abstractions are used by viewers to rapidly and effectively explore and analyze the underlying purchase orders data.
By Amit Prakash Sawant, Christopher G. Healey, Dongfeng Chen, Rada Chirkova, March 2009
By Joonghoon Lee, December 2008
By Shahriar Manzoor, June 2008
By Chris Jordan, Oliver Baltzer, Sean Smith, August 2006
By Thomas Wright, December 2004
By Bryan Stroube, September 2003
By G. Michael Youngblood, June 1999
By Shawn Brown, November 1998
By Lynellen D. S. Perry, September 1998
By Phil Agre, May 1998
By Jack Wilson, May 1998
By Jack Wilson, April 1998
By Hal Berghel, October 1997
By George E. Hatoun, Brad Templeton, February 1996
By Lorrie Faith Cranor, February 1996
By Matt Rosenberg, November 1995
By Ben W. Brumfield, September 1995
By Sarah Elizabeth Burcham, September 1995
By Saveen Reddy, September 1994