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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao http://dx.doi.org/10...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1109/eidwt....
Article . 2012 . Peer-reviewed
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Massive Processing of Activity Logs of a Virtual Campus

Authors: Fatos Xhafa; Juan Jose Ruiz; Santi Caballé; Evjola Spaho; Leonard Barolli; Rozeta Miho;

Massive Processing of Activity Logs of a Virtual Campus

Abstract

Online web-based application that heavily require user interaction, either among users or among users and the application, generate huge amounts of data. Recording such user interaction data, usually in the form of log data files, could be very useful for different purposes such as user modelling, user activity analysis, data analytics, security, monitoring, etc. However, such data is not ready to be analysed due log files are to be pre-processed and cleaned up from redundant and futile information. Due to the large amounts of data generated daily, the massive processing is a foremost step in extracting useful information from log data files. In this work we study the viability of massive processing of log data files of a real Virtual Campus using different distributed infrastructures. More precisely, we study the time performance of processing daily log files of a Virtual Campus using cluster computing(under Open Grid Engine) and Planet Lab platform. The study reveals the complexity and challenges of massive processing in the big data era.

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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