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Published Articles >> Table of Contents >> Abstract
27th International Conference on Distributed Computing Systems Workshops (ICDCSW'07)
p. 14
Group-aware Stream Filtering
Ming Li, Dartmouth College, USA
David Kotz, Dartmouth College, USA
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDCSW.2007.38
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| Abstract |
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In this paper we are concerned with disseminating
high-volume data streams to many simultaneous
context-aware applications over a low-bandwidth wireless
mesh network. For bandwidth efficiency, we propose
a group-aware stream filtering approach, used in conjunction
with multicasting, that exploits two overlooked,
yet important, properties of these applications: 1) many
applications can tolerate some degree of "slack" in their
data quality requirements, and 2) there may exist multiple
subsets of the source data satisfying the quality needs
of an application. We can thus choose the "best alternative"
subset for each application to maximize the
data overlap within the group to best benefit from multicasting.
An evaluation of our prototype implementation
shows that group-aware data filtering can save bandwidth
with low CPU overhead.
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 Additional Information
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Index Terms- data dissemination, overlay multicasting,
data filtering, bandwidth reduction
Citation:
Ming Li, David Kotz,
"Group-aware Stream Filtering,"
icdcsw,
p. 14,
27th International Conference on Distributed Computing Systems Workshops (ICDCSW'07),
2007
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