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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Bibliographic Details

Published in:	2015 IEEE Fourth Symposium on Network Cloud Computing and Applications (NCCA) pp. 59 - 66
Main Authors:	Anceaume, Emmanuelle, Busnel, Yann, Rivetti, Nicolo
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.06.2015
Subjects:	Approximation algorithms Approximation methods Computational modeling Computer aided software engineering Data models Data stream model Estimation Frequency estimation randomized approximation algorithm
ISBN:	9781467377416, 1467377414
Online Access:	Get full text
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