A Survey of Distributed Clustering Algorithms

• Published in: 2012 International Conference on Industrial Control and Electronics Engineering pp. 1142 - 1145
• Main Authors: Mo Hai, Shuyun Zhang, Lei Zhu, Yue Wang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2012
• Subjects: Accuracy; Algorithm design and analysis; centralized clustering; Classification algorithms; clustering accuracy; Clustering algorithms; clustering time; Computers; distributed clustering; Distributed databases; Partitioning algorithms
• ISBN: 1467314501; 9781467314503
• DOI: 10.1109/ICICEE.2012.303

Clustering is to divide a set of objects into multiple classes, and each class is made up of similar objects. Traditional centralized clustering algorithms cluster objects stored in a single site, but it cannot satisfy the clustering requirements when objects are distributed. Distributed clustering algorithms can satisfy this need, which extracts a classification mode from distributed objects. This paper classifies and analyzes typical distributed clustering algorithms. Two data sets-Iris and Wine are used to compare several distributed clustering algorithms from two metrics: clustering accuracy and clustering time.