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Distributed monitoring methods address the difficult problem of continuously approximating functions over distributed streams, while minimizing the communication cost. However, existing methods are concerned with the approximation of a single function at a time. Employing these methods to track multiple functions will multiply the communication volume, thus eliminating their advantage in the first place. We introduce a novel approach that can be applied to multiple functions. Our method applies a communication reduction scheme to the set of functions, rather than to each function independently, keeping a low communication volume. Evaluation on several real-world datasets shows that our method can track many functions with reduced communication, in most cases incurring only a negligible increase in communication over distributed approximation of a single function.

Fri 23 Jun

debs-2017-papers
14:10 - 15:20: DEBS Research Papers - Session 6: Models and Analysis for Understanding Distributed and Event-Based Systems at Sala d'Actes, Vertex Building
Chair(s): Alessandro MargaraPolitecnico di Milano
debs-2017-papers14:10 - 14:33
Talk
Fabrice StarksUniversity of Oslo, Thomas PlagemannUniversity of Oslo, Stein KristiansenUniversity of Oslo
debs-2017-papers14:33 - 14:56
Talk
Vincenzo GulisanoChalmers University of Technology, Alessandro Vittorio PapadopoulosMälardalen University, Yiannis NikolakopoulosChalmers University of Technology, Marina PapatriantafilouChalmers University of Technology, Philippas TsigasChalmers University of Technology
debs-2017-papers14:56 - 15:20
Talk
Arnon LazersonTechnion, Moshe GabelTechnion, Daniel KerenHaifa University, Assaf SchusterTechnion