| EPSRC Reference: |
GR/L87958/02 |
| Title: |
VIRTUAL 'DATA MINING' OF AN ATM NETWORK |
| Principal Investigator: |
Burn-Thornton, Dr K |
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| Department: |
Computer Science |
| Organisation: |
Durham, University of |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
17 July 2000 |
Ends: |
16 April 2001 |
Value (£): |
28,920
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| EPSRC Research Topic Classifications: |
| Networks & Distributed Systems |
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Summary on Grant Application Form |
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There is presently no means by which an ATM network engineer may explore the different layers of an ATM network and determine the health of the network at these various levels by watching the traffic flowing through the network and the problems it encounters. Combining the emerging technologies of Data Mining and Virtual Reality into a new research field of Virtual Data Mining will enable an engineer to complete such a task using a Virtual Data Mining tool. The primary aim of this research is to investigate the feasibility of developing a Virtual Data Mining tool consisting of a Virtual Reality representation of an ATM network through which the user may fly and glean performance information from real world systems. Depending on the speed that the user is flying through the network, and the layer at which the user is flying, various details of performance information will be available e.g. the slower the speed the greater the detail of performance information which will be available, and the lower the layer in the network the greater the detail of performance information which will be available. This performance information will be made available to the user via optimal visualisation techniques.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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