On-line Rule Updating System Using Evolutionary Computation for Managing Distributed Database

Wirarama Wedashwara, Shingo Mabu, Masanao Obayashi, Takashi Kuremoto
Corresponding Author
Wirarama Wedashwara
Available Online 1 September 2015.
Genetic Network Programming, Rule Based Clustering, Cluster Optimization
This research proposes a decision support system of database cluster optimization using genetic network programming (GNP) with on-line rule based clustering. GNP optimizes cluster quality by reanalyzing weak points of each cluster and maintaining rules stored in each cluster. The maintenance of rules includes: 1) adding new relevant rules; 2) moving rules between clusters; and 3) removing irrelevant rules. The simulations focus on optimizing cluster quality response against several unbalanced data growth to the data-set that is working with storage rules. The simulation results of the proposed method show its priority comparing to GNP rule based clustering without on-line optimization.

© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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