Abstract
Large scale distributed computing infrastructure captures the use of high number of nodes, poor communication performance and continously varying resources that are not available at any time. In this paper, we focus on the different tools available for mining traces of the activities of such aforementioned architecture. We propose new techniques for fast management of a frequent itemset mining parallel algorithm. The technique allow us to exhibit statistical results about the activity of more that one hundred PCs connected to the web.
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© 2005 Springer-Verlag Berlin Heidelberg
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Cérin, C., Koskas, M. (2005). Mining Traces of Large Scale Systems. In: Hobbs, M., Goscinski, A.M., Zhou, W. (eds) Distributed and Parallel Computing. ICA3PP 2005. Lecture Notes in Computer Science, vol 3719. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564621_15
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DOI: https://doi.org/10.1007/11564621_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29235-7
Online ISBN: 978-3-540-32071-5
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