A Distributed Information Divergence Estimation over Data Streams

In this paper, we consider the setting of large scale distributed systems, in which each node needs to quickly process a huge amount of data received in the form of a stream that may have been tampered with by an adversary. In this situation, a fundamental problem is how to detect and quantify the a...

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Veröffentlicht in:	IEEE transactions on parallel and distributed systems Jg. 25; H. 2; S. 478 - 487
Hauptverfasser:	Anceaume, Emmanuelle, Busnel, Yann
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.02.2014 Institute of Electrical and Electronics Engineers
Schlagworte:	Algorithm design and analysis Approximation algorithms byzantine adversary Computational modeling Computer Science Data models Data stream Data Structures and Algorithms Distributed, Parallel, and Cluster Computing Entropy Estimation Kullback-Leibler divergence performance analysis Radiation detectors randomized approximation algorithm Randomized approximation algorithm Data stream Divergence
ISSN:	1045-9219
Online-Zugang:	Volltext
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