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In grid computing environment, a balanced transaction scheduling is a NP-hard problem. In this paper, a technique for load-balanced transaction scheduling using Gaussian mixture model-ant colony optimization algorithm is proposed. Gaussian mixture model, which is based on Gaussian density functions, provides clustering characteristics. Our proposed algorithm uses this clustering method to identify the cluster of nodes with less nodes and uses ant colony optimization to find out the appropriate node for the final selection. The proposed algorithm outperforms the existing algorithms.

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Load Balanced Transaction Scheduling Using Gaussian Mixture Model-Ant Colony Optimization

  • 会议论文

  • 发表日期：

    2025年

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  • Amisha Gupta,
  • Satish Chander Sharma,
  • Divya Jyoti,
  • Ritika Verma,
  • Mohammad Azeem,
  • Dharmendra Prasad Mahato

摘要

In grid computing environment, a balanced transaction scheduling is a NP-hard problem. In this paper, a technique for load-balanced transaction scheduling using Gaussian mixture model-ant colony optimization algorithm is proposed. Gaussian mixture model, which is based on Gaussian density functions, provides clustering characteristics. Our proposed algorithm uses this clustering method to identify the cluster of nodes with less nodes and uses ant colony optimization to find out the appropriate node for the final selection. The proposed algorithm outperforms the existing algorithms.