Back to Top

■ One for All and All for One: Simultaneous Approximation of Multiple Functions over Distributed Streams

Lazerson, A., Gabel, M., Keren, D., & Schuster, A. (2017, June). One for All and All for One: Simultaneous Approximation of Multiple Functions over Distributed Streams. In Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems (pp. 203-214). ACM.

Abstract

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.

Bibtex Entry.

@inproceedings{Lazerson:2017:OOS:3093742.3093918,
 author = {Lazerson, Arnon and Gabel, Moshe and Keren, Daniel and Schuster, Assaf},
 title = {One for All and All for One: Simultaneous Approximation of Multiple Functions over Distributed Streams},
 booktitle = {Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems},
 series = {DEBS '17},
 year = {2017},
 isbn = {978-1-4503-5065-5},
 location = {Barcelona, Spain},
 pages = {203--214},
 numpages = {12},
 url = {http://doi.acm.org/10.1145/3093742.3093918},
 doi = {10.1145/3093742.3093918},
 acmid = {3093918},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {continous approximation, distriubted streams, multiple fuinctions},
}