Link technologies in today's data center networks impose a fundamental trade-off between reach, power, and reliability. Copper links are power-efficient and reliable but have very limited reach (< 2 m). Optical links offer longer reach but at the expense of high power consumption and lower reliability. As network speeds increase, this trade-off becomes more pronounced, constraining future scalability.

We have developed Environmental Scenario Search Engine (ESSE) for parallel data mining of a set of conditions inside distributed, very large databases from multiple environmental domains. The prime goal for ESSE design is to allow a user to query the environmental data archives in human linguistic terms. The mapping between the human language and the computer system involves fuzzy logic. Imagine for example that the end user doesn't need all of the weather data covering the Moscow region for the last 50 years, but rather needs an example of an atmospheric front near Moscow. Further imagine that this user needs satellite images of the front and he wants to know how often such fronts occur or if they have been increasing in the last 10 years. ESSE data mining and visualization portal combines metadata search, interactive fuzzy scenario query editor and event visualization system. Visualization system is implemented as MS Windows application based on NASA World Wind 3D globe and as a web application built upon OGC WMS and Microsoft Virtual Earth control.

Abstract The solar‐terrestrial physics distributed database for the ICSU World Data Centers, and the NCEP/NCAR climate re‐analysis data have been integrated into standard Grid environments using the OGSA‐DAI framework. A set of algorithms and software tools for distributed querying and mining environmental archives using the UNIDATA Common Data Model concepts has been developed. In addition, the toolkit enables querying the data using meaningful ‘human linguistic’ terms. Copyright © 2007 John Wiley & Sons, Ltd.