Estimating the Frequency of Data Items in Massive Distributed Streams

We investigate the problem of estimating on the fly the frequency at which items recur in large scale distributed data streams, which has become the norm in cloud-based application. This paper presents CASE, a combination of tools and probabilistic algorithms from the data streaming model. In this m...

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Vydané v:	2015 IEEE Fourth Symposium on Network Cloud Computing and Applications (NCCA) s. 59 - 66
Hlavní autori:	Anceaume, Emmanuelle, Busnel, Yann, Rivetti, Nicolo
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.06.2015
Predmet:	Approximation algorithms Approximation methods Computational modeling Computer aided software engineering Data models Data stream model Estimation Frequency estimation randomized approximation algorithm
ISBN:	9781467377416, 1467377414
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