Title:
Real-Time Visualization in Distributed Computational Laboratories
Real-Time Visualization in Distributed Computational Laboratories
Author(s)
King, Davis
Schwan, Karsten
Eisenhauer, Greg S.
Plale, Beth
Isert, Carsten
Schwan, Karsten
Eisenhauer, Greg S.
Plale, Beth
Isert, Carsten
Advisor(s)
Editor(s)
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Abstract
Large data volumes cannot be transported, processed or displayed in
real-time unless we apply to them general or application-specific
compression and filtering techniques. In addition, when multiple end users
inspect such data sets or when multiple programs access or consume them,
data distribution and display should be performed differentially, in
accordance with the queries generated by programs or end users. Finally, if
dynamic access queries cannot be formulated precisely, then they must be
refined as they progress in order to avoid unnecessary data retrievals,
transfers, and information overload for programs or end users with
uninteresting or unimportant data.
The principal idea of our research is to create Active User Interfaces
(AUIs) that continuously emit events describing their internal states and/or
current information needs. Based on these events, we then develop methods
for controlling the information streams directed at these interfaces, for
single and for multiple, collaborating end users. The purposes of stream
control are twofold. First, stream control is performed to deal with
heterogeneous underlying hardware and software systems, where streams may
originate at secondary storage media or may be generated dynamically, may
have to be moved across the Internet or may utilize local area or high
performance interconnects, and where collaborating user interfaces may range
from low end PC-based displays to high end immersive visualization engines.
Second, stream control aims to achieve scalability for user interfaces to
large-scale, complex data streams directed at them, by offloading
computations from visualizations to information generators or to information
routing sites, to dynamically migrate such computations to appropriate
locations, and to adapt these computations in order to effect tradeoffs in
the amount of data moved across network links vs. the computations required
when performing data rendering, compression, filtering, and routing actions.
Sponsor
Date Issued
1999
Extent
245251 bytes
Resource Type
Text
Resource Subtype
Technical Report