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Related Concept Videos

Interpreting Run Charts01:25

Interpreting Run Charts

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Related Experiment Videos

Visual Analysis of Cloud Computing Performance Using Behavioral Lines.

Chris Muelder, Biao Zhu, Wei Chen

    IEEE Transactions on Visualization and Computer Graphics
    |March 9, 2016
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a visual analysis method for cloud computing systems. It effectively identifies performance bottlenecks and system anomalies using multivariate time series data.

    Related Experiment Videos

    Area of Science:

    • Computer Science
    • Data Science
    • Systems Engineering

    Background:

    • Cloud computing is crucial for Big Data analytics, requiring robust monitoring.
    • Large-scale cloud systems present challenges in performance analysis due to data volume and privacy.
    • Existing tools are inadequate for studying large-scale, multidimensional cloud system data.

    Purpose of the Study:

    • To present a visual-based analysis approach for understanding cloud computing system performance and behavior.
    • To address the lack of adequate tools for analyzing multivariate time series data from cloud systems.

    Main Methods:

    • Developed a visual analysis approach based on similarity measures and a layout method.
    • Collected profile data, including CPU load, memory, and network usage, as multivariate time series.
    • Implemented a system with multiple linked views for interactive data exploration at various detail levels.

    Main Results:

    • Visualizing numerous behavioral lines revealed distinct patterns indicating performance bottlenecks.
    • The approach effectively identified trends and anomalies in cloud computing systems.
    • Case studies using datasets from two cloud systems validated the approach's effectiveness.

    Conclusions:

    • The visual-based analysis approach is effective for understanding and analyzing cloud computing system performance.
    • This method aids in identifying performance bottlenecks and system anomalies in large-scale cloud environments.
    • The interactive, multi-view system facilitates detailed exploration of cloud system behavior.