A Hierarchical and Grid Based Clustering Method for Distributed Systems (Hgd Cluster)
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 6
Abstract
Abstract: In distributed peer-to-peer systems, huge amount of data are dispersed. Grouping of those data from multiple sources is a tedious task. By applying effective data mining techniques the clustering of distributed datais become ease and this decreases the hurdles of clustering due to processing, storage, and transmission costs. To perform a dynamic distributed clustering, a fully decentralized clustering method has been proposed. HGDCluster can cluster a data set which is dispersed among a large number of nodes in a distributed environment using hierarchal and grid based clustering techniques. When nodes are fully asynchronous and decentralized and also adaptable to stir, then HGD cluster will apply. The general design principles employed in the proposed algorithm also allow customization for other classes of clustering. It is fully capable of clustering dynamic anddistributed data sets. Using the algorithm, every node can maintain summarized views of the dataset. Customizing HGD Cluster for execution of the hierarchal-based and grid-based clustering methods on thesummarized views is the main aim of the proposed system. Coping with dynamic data is made possible by gradually adapting the clustering model.
Authors and Affiliations
Mr. A. Venugopal M. Sc. , M. Phil, , V. Sujatha Veni.
Keywords
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