archivedAI Testing and Quality Assurance

Modeling Network Latency

Research on modeling network latency for distributed systems as a real-world case study of various distribution families. Explores statistical modeling approaches for understanding and predicting network performance in distributed computing environments.

Key Research Findings

Network latency exhibits complex multi-modal distributions requiring sophisticated modeling

Traditional Gaussian assumptions fail for real-world network performance data

Mixture models and heavy-tailed distributions better capture latency characteristics

Statistical modeling enables predictive performance optimization in distributed systems

Technical Details & Impact

Technologies Used

StatisticsMathematicaNetwork AnalysisDistributed Systems

Research Status

Last updated: 2015

Research Impact

Provided foundational insights into modeling network performance, influencing the design of robust distributed systems by accounting for real-world latency characteristics.

This research is part of ongoing open-source development. Contributions, discussions, and collaborations are welcome.