A Review on Probabilistic Analysis of Distributed Systems Using Monte Carlo Approach

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@article{1706130,
      author = {Esosa Enoyoze, Ijegwa David Acheme},
      title = {A Review on Probabilistic Analysis of Distributed Systems Using Monte Carlo Approach},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {2},
      pages = {169-183},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706130.pdf},
      abstract = {The inherent complexity and uncertainty in distributed systems necessitate robust analytical methods to evaluate their performance, reliability, and scalability. The Monte Carlo simulation, a probabilistic technique based on random sampling and statistical modeling, offers a versatile approach for such analysis. This review systematically examines the application of Monte Carlo methods in the context of distributed systems, encompassing recent advancements, methodologies, and practical implementations. We conducted a comprehensive literature search across leading databases, focusing on studies that utilize Monte Carlo simulations for various aspects of distributed systems. Our analysis reveals that Monte Carlo methods are extensively applied for performance analysis, reliability assessment, fault tolerance, and scalability evaluation. Through detailed case studies, we illustrate the practical utility and impact of these simulations on different distributed system architectures, including cloud computing, peer-to-peer networks, and grid computing. Despite their advantages, Monte Carlo simulations face challenges such as high computational demands and the need for large sample sizes. We discuss these challenges and propose future directions to enhance the effectiveness and efficiency of Monte Carlo simulations in distributed systems. This study provides valuable insights and recommendations for researchers and practitioners aiming to optimize distributed systems using probabilistic analysis.},
      keywords = {Probabilistic Analysis, Distributed Systems, Monte Carlo Simulation, Reliability, Performance Analysis, Review},
      month = {August},
  }