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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Vydané v:	IEEE transactions on parallel and distributed systems Ročník 25; číslo 2; s. 478 - 487
Hlavní autori:	Anceaume, Emmanuelle, Busnel, Yann
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.02.2014 Institute of Electrical and Electronics Engineers
Predmet:	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
On-line prístup:	Získať plný text
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