@inproceedings{li:wwasn07,
    author = {Ming Li and David Kotz},
    title = {Group-aware Stream Filtering},
    booktitle = {Proceedings of the Fourth Workshop on Wireless Ad hoc and Sensor
Networks (WWASN)},
    year = {2007},
    month = {June},
    publisher = {IEEE Computer Society Press},
    copyright = {IEEE},
    address = {Toronto},
    doi = {10.1109/ICDCSW.2007.38},
    url = {http://www.cs.dartmouth.edu/~dfk/papers/li-wwasn07.pdf},
    keyword = {wireless network, mobile computing, streaming data, sensor
network},
    abstract = {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
{\em 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.},
}