Ming Li and David Kotz. Group-aware Stream Filtering. In Proceedings of the Fourth Workshop on Wireless Ad hoc and Sensor Networks (WWASN), Toronto, June 2007. IEEE Computer Society Press. DOI 10.1109/ICDCSW.2007.38.

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 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.

Keywords: distributed computing

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Copyright © 2007 by IEEE.

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