Performance Evaluation of a Distributed Clustering Approach for Spatial Datasets

  • Malika BendechacheEmail author
  • Nhien-An Le-Khac
  • M-Tahar Kechadi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 845)


The analysis of big data requires powerful, scalable, and accurate data analytics techniques that the traditional data mining and machine learning do not have as a whole. Therefore, new data analytics frameworks are needed to deal with the big data challenges such as volumes, velocity, veracity, variety of the data. Distributed data mining constitutes a promising approach for big data sets, as they are usually produced in distributed locations, and processing them on their local sites will reduce significantly the response times, communications, etc. In this paper, we propose to study the performance of a distributed clustering, called Dynamic Distributed Clustering (DDC). DDC has the ability to remotely generate clusters and then aggregate them using an efficient aggregation algorithm. The technique is developed for spatial datasets. We evaluated the DDC using two types of communications (synchronous and asynchronous), and tested using various load distributions. The experimental results show that the approach has super-linear speed-up, scales up very well, and can take advantage of the recent programming models, such as MapReduce model, as its results are not affected by the types of communications.


Distributed data mining Distributed computing Synchronous communication Asynchronous communication Spacial data mining Super-speedup 



The research work is conducted in the Insight Centre for Data Analytics, which is supported by Science Foundation Ireland under Grant Number SFI/12/RC/2289.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Malika Bendechache
    • 1
    Email author
  • Nhien-An Le-Khac
    • 2
  • M-Tahar Kechadi
    • 1
  1. 1.Insight Centre for Data AnalyticsUniversity College DublinBelfield, Dublin 04Ireland
  2. 2.University College DublinBelfield, Dublin 04Ireland

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