StreamGlobe: Adaptive query processing and optimization in streaming P2P environments

Recent research and development efforts show the increasing importance of processing data streams, not only in the context of sensor networks, but also in information retrieval networks. With the advent of various mobile devices being able to participate in ubiquitous (wireless) networks, a major challenge is to develop data stream management systems (DSMS) for information retrieval in such networks. In this paper, we present the architecture of our StreamGlobe system, which is focused on meeting the challenges of efficiently querying data streams in an ad-hoc network environment. StreamGlobe is based on a federation of heterogeneous peers ranging from small, possibly mobile devices to stationary servers. On this foundation, self-organizing network optimization and expressive in-network query processing capabilities enable powerful information processing and retrieval. Data streams in StreamGlobe are represented in XML and queried using XQuery. We report on our ongoing implementation effort and briefly show our research agenda.