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NSF PR 01-01 - January 5, 2001
Media contact:
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Tom Garritano
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(703) 292-8070
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tgarrita@nsf.gov
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Program contact:
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Tom Greene
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(703) 292-8950
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tgreene@nsf.gov
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This material is available primarily
for archival purposes. Telephone numbers
or other contact information may be out
of date; please see current contact information
at media
contacts.
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NSF Grant Extends Support for Interconnecting National
Research Networks
The National Science Foundation has awarded $2.5 million
dollars to the National Laboratory for Applied Network
Research (NLANR) to continue technical, engineering
and traffic analysis support to the high-performance
networking and applications communities. The grant
extends by one year NLANR’s original three year cooperative
agreement to support universities and institutions
in connecting to the nation’s research networks.
"Since being formed in 1997, NLANR has excelled at
developing tools, providing training, supporting individual
applications and offering network-usage information
to researchers in computer science and scientific
computing," said Thomas Greene, NSF senior program
director in the Advanced Networking Infrastructure
program. "These activities contribute to what is becoming
known as 'Cyber-Infrastructure,' which incorporates
more varied resources than just connectivity or computational
power. NSF is pleased to support this and similar
projects of such quality and focus."
NLANR is a collaboration of the National Center for
Supercomputing Applications (NCSA) at the University
of Illinois at Urbana-Champaign; the Pittsburgh Supercomputing
Center (PSC); the National Center for Atmospheric
Research (NCAR); and the San Diego Supercomputer Center
(SDSC). The partnership helps more than 170 NSF-funded
High-Performance Connections sites connect to and
use high-performance research network backbones like
NSF’s vBNS (very high performance Broadband Network
Services).
NLANR develops software to help scientific users and
network administrators, while designing analytical
tools to help networks run smoothly. The NLANR staff
works with researchers and staff at small- to mid-sized
campuses and with commercial service providers, resulting
in a broad impact on the networking and application
communities. The award will be divided among the following
three NLANR program teams:
- The Distributed Applications Support team at the
NCSA. This team helps researchers maximize performance
of their distributed applications. The team works
on networked applications that are computationally
intensive, including distributed data mining and
shared multimedia collaborative environments.
The staff delivers training sessions around the
country and demonstrate NLANR-developed tools
such as Iperf, Netlog, and Viznet.
- The Engineering Services Team, a collaboration
between the PSC and NCAR. This team provides engineering
support for the integration and use of advanced
network services between commercial providers
and campus infrastructures, while optimizing end-to-end
performance for applications over this integrated
environment. NLANR network engineers also develop
tools, such as Traffic Analysis and Automatic
Diagnosis (TAAD), to help improve network performance.
The team offers the NLANR On-Site program that
provides courseware and hands-on training tailored
for network engineers and disciplinary scientists.
- The Measurement And Network Analysis Team, based
at SDSC. This team has created a network-analysis
infrastructure by deploying both active and passive
measurement devices at more than 100 locations
across the networks. The team’s products include
statistical tools for analyzing and visualizing
traffic patterns. Working with performance and
flow measurements, the staff use packet information
to develop service models and measure network
efficiency.
For more information, see: http://www.nlanr.net/
For more information about ANIR, see: http://www.cise.nsf.gov/anir/
Additional press contacts:
Sean Fulton, PSC (412-268-7141/sfulton@psc.edu)
Mike Gannis, SDSC (858-534-5143/mgannis@sdsc.edu)
Karen Green, NCSA (217-265-0748/kareng@ncsa.edu)
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