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A Geometric Approach to Monitoring Threshold Functions Over Distributed Data Streams by Izchak Sharfman; Assaf Schuster; Daniel Keren is a Computer Science article available to read on EtoBox.

What is A Geometric Approach to Monitoring Threshold Functions Over Distributed Data Streams about?

Monitoring data streams in a distributed system is the focus of much research in recent years. Most of the proposed schemes, however, deal with monitoring simple aggregated values, such as the frequency of appearance of items in the streams. More involved challenges, such as the important task of feature selection (e.g., by monitoring the information gain of various features), still require very high communication overhead using naive, centralized algorithms. We present a novel geometric approach which reduces monitoring the value of a function (vis-à-vis a threshold) to a set of constraints applied locally on each of the streams. The constraints are used to locally filter out data increments that do not affect the monitoring outcome, thus avoiding unnecessary communication. As a result, our approach enables monitoring of arbitrary threshold functions over distributed data streams in an efficient manner. We present experimental results on real-world data which demonstrate that our algorithms are highly scalable, and considerably reduce communication load in comparison to centralized algorithms.

Who reads A Geometric Approach to Monitoring Threshold Functions Over Distributed Data Streams?

Author

Izchak Sharfman; Assaf Schuster; Daniel Keren

Publisher

ACM

Published

2007

Language

EN

Field

Computer Science (Physical Sciences)