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Erschienen in:

2018 | OriginalPaper | Buchkapitel

Mobile Agent-Based Frequent Pattern Mining for Distributed Databases

verfasst von : Yashaswini Joshi, Shashikumar G. Totad, R. B. Geeta, P. V. G. D. Prasad Reddy

Erschienen in: Intelligent Computing and Information and Communication

Verlag: Springer Singapore

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Abstract

In today’s world of globalization, business organizations produce information from many branch offices of their business while operating across the globe and hence lead to large chunk of distributed databases. There is an innate need to look at this distributed information that leverages the past, monitors the present, and predicts the future with accuracy. Mining large distributed databases using client–server model is time-consuming and sometimes impractical because it requires huge databases to be transferred over very long distances. Mobile agent technology is a promising alternative that addresses the issues of client–server computing model. In this paper, we have proposed an algorithm called MADFPM for frequent pattern mining of distributed databases that use mobile agents. We have shown that the performance of MADFPM is better compared to the conventional client–server approach.

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Vorheriges Kapitel ClustMap: A Topology-Aware MPI Process Placement Algorithm for Multi-core Clusters

Nächstes Kapitel A Hybrid Approach for Preprocessing of Imbalanced Data in Credit Scoring Systems

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Titel: Mobile Agent-Based Frequent Pattern Mining for Distributed Databases
verfasst von: Yashaswini Joshi
Shashikumar G. Totad
R. B. Geeta
P. V. G. D. Prasad Reddy
Verlag: Springer Singapore
Buch: Intelligent Computing and Information and Communication
Print ISBN: 978-981-10-7244-4

Electronic ISBN: 978-981-10-7245-1

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-981-10-7245-1_9

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