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Award Abstract #0215836
MRI: Acquisition of Wireless, Beowulf, and Distributed Computing Clusters
| NSF Org: |
CNS
Division of Computer and Network Systems
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| Initial Amendment Date: |
May 29, 2002 |
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| Latest Amendment Date: |
May 29, 2002 |
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| Award Number: |
0215836 |
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| Award Instrument: |
Standard Grant |
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| Program Manager: |
Rita V. Rodriguez
CNS Division of Computer and Network Systems
CSE Directorate for Computer & Information Science & Engineering
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| Start Date: |
September 1, 2002 |
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| Expires: |
August 31, 2005 (Estimated) |
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| Awarded Amount to Date: |
$142767 |
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| Investigator(s): |
Gary Lewandowski lewandow@cs.xu.edu (Principal Investigator)
Michael Goldweber (Co-Principal Investigator)
Elizabeth Johnson (Co-Principal Investigator)
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| Sponsor: |
Xavier University
3800 Victory Parkway
Cincinnati, OH 45207 513/745-3000
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| NSF Program(s): |
MAJOR RESEARCH INSTRUMENTATION
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| Field Application(s): |
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| Program Reference Code(s): |
HPCC, 9229, 9218, 1189
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| Program Element Code(s): |
1189
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ABSTRACT
EIA-0215836
Gary C. Lewandowski
Michael Goldweber
Elizabeth L. Johnson
Xavier University
MRI/RUI: Acquisition of Wireless, Beowulf, and Distributed Computing Clusters
This proposal from an REU institution, establishing a parallel and distributed computing research laboratory for CS faculty and students, includes
An ad hoc mobile network cluster (handheld PDA and labtops connecting without a server),
A Beowulf cluster ( a parallel computing cluster composed of off-the-shelf PCs with fast network connections between them), and
Workstations connected in typical network style.
With specific research activities that follow, the clusters will support the following areas:
A. Parallel and Distributed Computation on Ad Hoc Networks
1. Development of a serverless location protocol
2. Development of parallel applications for ad hoc networks on top of serverless SLP, and
3. Utilizing idle cycles of wireless devices
B. Parallel Algorithms for Graphs Coloring and Applications
1. Graph coloring heuristics
2. Historical study of the four-color theorem
C. Parallel Genetic Algorithms (an optimization techniques based on the idea of "survival of the fittest")
D. Language Support for Distributed Computing over Heterogeneous Networks
(support for distributed data structures in High Performance C++)
E. Distributed Database Systems
F. Distributed Virtual Shared Memory Architectures
G. High-Energy Astrophysics
H. Dynamics of complex systems
Depending on the configuration needed for a particular application, the three clusters will be combined into one heterogeneous distributed network or used as stand-alone parallel/distributed networks.
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