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Creators/Authors contains: "Pratik Poudel"

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  1. (, International Conference on Principles of Advanced Discrete Simulation (PADS))
    This study addresses the knowledge gap in request-level storage trace analysis by incorporating workload characterization, com- pression, and synthesis. The aim is to better understand workload behavior and provide unique workloads for storage system test- ing under different scenarios. Machine learning techniques like K-means clustering and PCA analysis are employed to understand trace properties and reduce manual workload selection. By gener- ating synthetic workloads, the proposed method facilitates simu- lation and modeling-based studies of storage systems, especially for emerging technologies like Storage Class Memory (SCM) with limited workload availability. 
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    Accepted Manuscript Full Text Available