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A hybrid model for improving response time in distributed data mining.

Shonali Krishnaswamy1, Seng W Loke, Arkady Zaslasvky

  • 1School of Computer Science and Software Engineering, Monash University, Melbourne 3145, Australia. Shonali.Krishnaswamy@infotech.monash.edu.au

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|December 29, 2004
PubMed
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This study introduces a hybrid distributed data mining (DDM) model using mobile agents and client-server methods to optimize response times. Experimental results demonstrate the effectiveness of this approach for faster data processing.

Area of Science:

  • Computer Science
  • Data Mining
  • Distributed Systems

Background:

  • Optimizing response time is crucial in distributed data mining (DDM).
  • Existing DDM models face challenges in balancing computation and communication costs.
  • Mobile agent and client-server approaches offer potential but have limitations.

Purpose of the Study:

  • To present a novel hybrid distributed data mining (DDM) model.
  • To optimize the response time of DDM systems.
  • To reduce overall system latency through an integrated approach.

Main Methods:

  • Developed a hybrid DDM model combining mobile agent and client-server strategies.
  • Implemented a costing strategy using accurate a priori estimates for computation and communication.

Related Experiment Videos

  • Conducted experimental evaluations to validate the model's performance.

    • Main Results:

    • The hybrid model effectively reduces overall response time.
    • Accurate estimation of computation and communication components aids optimization.
    • Experimental data supports the model's efficiency and effectiveness.

    Conclusions:

    • The proposed hybrid DDM model offers a significant improvement in response time optimization.
    • Accurate cost estimation is a key factor in achieving efficient distributed data mining.
    • This approach provides a viable solution for reducing latency in DDM applications.