Mining data streams is a critical task of actual Big Data applications. Usually, data stream mining algorithms work on resource-constrained environments, which call for novel requirements like availability of resources and adaptivity. Following this main trend, in this paper we propose a distributed data stream classification technique that has been tested on a real sensor network platform, namely, Sun SPOT. The proposed technique shows several points of research innovation, with are also confirmed by its effectiveness and efficiency assessed in our experimental campaign.
CITATION STYLE
Cuzzocrea, A., Gaber, M. M., & Shiddiqi, A. M. (2015). Distributed classification of data streams: An adaptive technique. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9263, pp. 296–309). Springer Verlag. https://doi.org/10.1007/978-3-319-22729-0_23
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