ResiliLens: An AI-Driven Framework for Simulation and Failure Analysis in Distributed Systems

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@article{1718118,
      author = {Vedant Meshram, Ashwini Garkhedkar},
      title = {ResiliLens: An AI-Driven Framework for Simulation and Failure Analysis in Distributed Systems},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {11},
      pages = {3746-3751},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1718118.pdf},
      abstract = {Distributed systems are increasingly complex due to the integration of heterogeneous components such as cloud services, IoT devices, and network infrastructures. Ensuring reliability and performance under varying conditions remains a significant challenge. This paper proposes ResiliLens, a conceptual framework that leverages simulation techniques and artificial intelligence to analyze distributed system behavior under failure scenarios. The framework enables virtual system modeling, failure injection, performance evaluation, and AI-driven recommendations for system improvement. By providing an intuitive and unified approach, ResiliLens aims to simplify distributed system validation and enhance reliability through intelligent insights. Modern distributed systems form the backbone of applications such as smart cities, cloud computing, and real-time analytics. These systems involve multiple interconnected components operating across diverse environments. However, their complexity introduces challenges in ensuring performance, reliability, and fault tolerance.},
      month = {May},
      doi = {https://doi.org/10.64388/IREV9I11-1718118}
  }