@inproceedings{6a52ec4dc64c4200bf29655c57e84121,
title = "Reducing Communication and Merging Overheads for Distributed Clustering Algorithms on the Cloud",
abstract = "Many distributed clustering algorithms have been proposed to speed up data clustering on huge database. However, the existing distributed clustering algorithms still suffer from many issues on distributed system such as data synchronization, insufficient scalability, and maintenance difficulties. In this paper, we propose two distributed clustering algorithms named DDC and DGC, which are based on the cloud computing technique. The main ideas of proposed algorithms are to achieve load balance according to an efficient data partition, to cluster more data on many machines in parallel without data dependency, and to merge the result on a machine efficiently with minimal information overlap. The experimental results show that DDC and DGC are able to reduce the execution time and achieve great scalability on the cloud.",
author = "Chen, {Chun Chieh} and Chen, {Tze Yu} and Huang, {Jen Wei} and Chen, {Ming Syan}",
year = "2016",
month = apr,
day = "8",
doi = "10.1109/CCBD.2015.9",
language = "English",
series = "Proceedings - 2015 International Conference on Cloud Computing and Big Data, CCBD 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "41--48",
booktitle = "Proceedings - 2015 International Conference on Cloud Computing and Big Data, CCBD 2015",
address = "United States",
note = "International Conference on Cloud Computing and Big Data, CCBD 2015 ; Conference date: 04-11-2015 Through 06-11-2015",
}