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.
Original language | English |
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Title of host publication | DEBS 2017 - Proceedings of the 11th ACM International Conference on Distributed Event-Based Systems |
Publisher | Association for Computing Machinery, Inc |
Pages | 203-214 |
Number of pages | 12 |
ISBN (Electronic) | 9781450350655 |
DOIs | |
State | Published - 8 Jun 2017 |
Event | 11th ACM International Conference on Distributed Event-Based Systems, DEBS 2017 - Barcelona, Spain Duration: 19 Jun 2017 → 23 Jun 2017 |
Publication series
Name | DEBS 2017 - Proceedings of the 11th ACM International Conference on Distributed Event-Based Systems |
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Conference
Conference | 11th ACM International Conference on Distributed Event-Based Systems, DEBS 2017 |
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Country/Territory | Spain |
City | Barcelona |
Period | 19/06/17 → 23/06/17 |
Bibliographical note
Publisher Copyright:© 2017 ACM.
Keywords
- Continous approximation
- Distriubted streams
- Multiple fuinctions
ASJC Scopus subject areas
- Computer Networks and Communications
- Hardware and Architecture
- Control and Systems Engineering
- Software