Performance Optimization and Hybrid Models in Distributed Data Mining Using ZeroMQ and MPI-2

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@article{1700138,
      author = {Hitesh Ninama},
      title = {Performance Optimization and Hybrid Models in Distributed Data Mining Using ZeroMQ and MPI-2},
      journal = {Iconic Research And Engineering Journals},
      year = {2018},
      volume = {1},
      number = {7},
      pages = {73-79},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1700138.pdf},
      abstract = {This paper presents a hybrid communication model that integrates ZeroMQ and MPI-2 to optimize performance and scalability in distributed data mining systems. By leveraging ZeroMQ for high-level coordination and MPI-2 for low-level parallel computation, the proposed methodology achieves significant improvements in execution time, throughput, and resource utilization. Experimental results demonstrate the effectiveness of this approach, highlighting its potential to enhance the efficiency of distributed data mining tasks. This hybrid model addresses the limitations of traditional methods and provides a robust framework for future research and practical implementations in distributed data mining.},
      keywords = {Distributed Data Mining, ZeroMQ, MPI-2, Performance Optimization, Hybrid Models, Scalability, Resource Utilization},
      month = {January},
  }